{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "cellView": "form",
    "colab": {},
    "colab_type": "code",
    "id": "8kAqKkITtUc4"
   },
   "outputs": [],
   "source": [
    "#@title License\n",
    "# Copyright 2019 BDL Benchmarks Authors. All Rights Reserved.\n",
    "#\n",
    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "# you may not use this file except in compliance with the License.\n",
    "# You may obtain a copy of the License at\n",
    "#\n",
    "#    http://www.apache.org/licenses/LICENSE-2.0\n",
    "#\n",
    "# Unless required by applicable law or agreed to in writing, software\n",
    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or  implied.\n",
    "# See the License for the specific language governing permissions and\n",
    "# limitations under the License.\n",
    "# ============================================================================"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "HPGNWFrStdUh"
   },
   "source": [
    "# Bayesian Deep Learning Benchmarks\n",
    "\n",
    "**Bayesian Deep Learning Benchmarks** (BDL Benchmarks or `bdlb` for short), is an open-source framework that aims to bridge the gap between the design of deep probabilistic machine learning models and their application to real-world problems, hosted on [GitHub](https://github.com/OATML/bdl-benchmarks).\n",
    "\n",
    "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
    "  <td>\n",
    "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/OATML/bdl-benchmarks/blob/alpha/notebooks/diabetic_retinopathy_diagnosis.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
    "  </td>\n",
    "  <td>\n",
    "    <a target=\"_blank\" href=\"https://github.com/OATML/bdl-benchmarks/blob/alpha/notebooks/diabetic_retinopathy_diagnosis.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n",
    "  </td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 119
    },
    "colab_type": "code",
    "id": "tqDZ8aRjtbzx",
    "outputId": "76e3fc06-a64c-4bbc-e05a-e35044f7dea1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[K     |████████████████████████████████| 348.9MB 108kB/s \n",
      "\u001b[K     |████████████████████████████████| 1.1MB 47.0MB/s \n",
      "\u001b[K     |████████████████████████████████| 686kB 43.3MB/s \n",
      "\u001b[K     |████████████████████████████████| 3.1MB 54.4MB/s \n",
      "\u001b[K     |████████████████████████████████| 501kB 51.5MB/s \n",
      "\u001b[?25h  Building wheel for bdlb (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
     ]
    }
   ],
   "source": [
    "#@title Dependencies & Prerequisites\n",
    "!pip install --quiet git+https://github.com/OATML/bdl-benchmarks.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "I6zWFOYjuWFf",
    "outputId": "fe19f8b4-b0e2-496a-927f-051729f476fa"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SUCCESS: Found GPU: /device:GPU:0\n"
     ]
    }
   ],
   "source": [
    "#@title Imports\n",
    "\n",
    "from __future__ import absolute_import\n",
    "from __future__ import division\n",
    "from __future__ import print_function\n",
    "\n",
    "import os\n",
    "import functools\n",
    "\n",
    "import numpy as np\n",
    "import scipy.stats\n",
    "import tensorflow as tf\n",
    "tfk = tf.keras\n",
    "tfkl = tfk.layers\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "if tf.test.gpu_device_name() != \"/device:GPU:0\":\n",
    "  raise OSError(\"GPU device not found\")\n",
    "else:\n",
    "  print(\"SUCCESS: Found GPU: {}\".format(tf.test.gpu_device_name()))\n",
    "\n",
    "import bdlb\n",
    "from bdlb.core.plotting import leaderboard\n",
    "from bdlb.core.constants import DIABETIC_RETINOPATHY_DIAGNOSIS_URL_MEDIUM\n",
    "from bdlb.core.constants import LEADERBOARD_DIR_URL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "rlsNu6D2krz9"
   },
   "source": [
    "## [Diabetic Retinopathy Diagnosis Benchmark](https://github.com/OATML/bdl-benchmarks/tree/alpha/baselines/diabetic_retinopathy_diagnosis)\n",
    "\n",
    "The benchmark that we use in this example is built on the [Kaggle Diabetic Retinopathy (DR) Detection Challenge data](https://www.kaggle.com/c/diabetic-retinopathy-detection/overview).\n",
    "It consists of 35,126 training images and 53,576 test images. We hold-out 20% of the training data as a validation set.\n",
    "Each image is graded by a specialist on the following scale: 0 -- No DR, 1 -- Mild DR, 2 -- Moderate DR, 3 -- Severe DR and 4 -- Proliferative DR.\n",
    "We recast the 5-class classification task as binary classification which is easily applicable to any BDL classification algorithm by asking the user to classify whether each image has sight-threatening DR, which is defined as Moderate DR or greater (classes 2-4) following [_Leibig et al._](https://www.nature.com/articles/s41598-017-17876-z.pdf).\n",
    "The data are unbalanced, with  only 19.6% of the training set and 19.2% of the test set having a positive label."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 170
    },
    "colab_type": "code",
    "id": "eVTyIRGC2paE",
    "outputId": "6baac404-cc88-4dc1-907e-110c013ab1b7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading...\n",
      "From: https://drive.google.com/uc?id=1WAvS-pQsVLxUJiClmKLnVNQkoKmRt2I_\n",
      "To: /scratch/anglos/bdl-benchmarks/notebooks/medium.zip\n",
      "685MB [00:10, 66.3MB/s] \n",
      "Downloading...\n",
      "From: https://drive.google.com/uc?id=1LQeAfqMQa4lot09qAuzWa3t6attmCeG-\n",
      "To: /scratch/anglos/bdl-benchmarks/notebooks/leaderboard.zip\n",
      "100%|######################################| 4.64k/4.64k [00:00<00:00, 8.03MB/s]\n"
     ]
    }
   ],
   "source": [
    "#@title Fetch Data (in TFRecords) & Leaderboard\n",
    "\n",
    "!pip install --quiet --upgrade gdown\n",
    "!gdown $DIABETIC_RETINOPATHY_DIAGNOSIS_URL_MEDIUM\n",
    "!mkdir -p data/diabetic_retinopathy_diagnosis\n",
    "!unzip -qq medium.zip\n",
    "!mv medium data/diabetic_retinopathy_diagnosis\n",
    "!rm -rf medium.zip\n",
    "\n",
    "!gdown $LEADERBOARD_DIR_URL\n",
    "!unzip -qq leaderboard.zip\n",
    "!rm -rf leaderboard.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "tHrQJxcKAO1T"
   },
   "outputs": [],
   "source": [
    "#@title Hyperparameters { display-mode: \"form\" }\n",
    "BATCH_SIZE = 16 #@param {type:\"integer\"}\n",
    "NUM_EPOCHS = 10 #@param {type:\"slider\", min:1, max:100, step:1}\n",
    "DROPOUT_RATE = 0.1 #@param {type:\"slider\", min:0, max:1.0, step:0.05}\n",
    "NUM_MCDROPOUT_SAMPLES = 10 #@param {type:\"integer\"}\n",
    "\n",
    "LEVEL = \"medium\" #@param [\"medium\"]\n",
    "\n",
    "input_shape = {\"medium\": (256, 256, 3),\n",
    "               \"realworld\": (512, 512, 3)}[LEVEL]\n",
    "learning_rate = 1e-3\n",
    "l2_reg = 5e-5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "cellView": "form",
    "colab": {},
    "colab_type": "code",
    "id": "C9wxpm_t-hWX"
   },
   "outputs": [],
   "source": [
    "#@title Helper Functions\n",
    "\n",
    "def visualize_tfdataset(tfdataset, num_samples):\n",
    "  \"\"\"Visualizes `num_samples` from the `tfdataset`.\"\"\"\n",
    "  \n",
    "  def to01(image):\n",
    "    \"\"\"Normalizes image to float [0, 1].\"\"\"\n",
    "    min_ = np.min(image)\n",
    "    max_ = np.max(image)\n",
    "    return (image - min_) / (max_ - min_)\n",
    "  \n",
    "  for X, y in tfdataset.take(1):\n",
    "    images = X.numpy()\n",
    "    labels = y.numpy()\n",
    "    B, _, _, _ = images.shape\n",
    "    num_samples = min(num_samples, B)\n",
    "    fig, axes = plt.subplots(figsize=(2.0*num_samples, 2.0), ncols=num_samples)\n",
    "    for i in range(num_samples):\n",
    "      ax = axes[i]\n",
    "      ax.imshow(to01(images[i]))\n",
    "      ax.axis(\"off\")\n",
    "      ax.set(title=\"healthy\" if labels[i] == 0 else \"diseased\")\n",
    "    fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "BBe1ZqSMrRFt"
   },
   "source": [
    "### Benchmark API\n",
    "\n",
    "The benchmarks can be easily loaded using `bdlb.load(benchmark, level, data_dir, batch_size)`.\n",
    "All the data management (i.e. download, prepare, preprocess, load, batch and prefetch) is abstracted away from the user and is **compatible with any deep learning framework**!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "cellView": "both",
    "colab": {},
    "colab_type": "code",
    "id": "QuAFiSca1Jwq"
   },
   "outputs": [],
   "source": [
    "dtask = bdlb.load(\n",
    "    benchmark=\"diabetic_retinopathy_diagnosis\",\n",
    "    level=LEVEL,\n",
    "    batch_size=BATCH_SIZE,\n",
    "    data_dir=\"data\",\n",
    "    download_and_prepare=False,\n",
    ")\n",
    "ds_train, ds_validation, ds_test = dtask.datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "colab_type": "code",
    "id": "oTfM0DD7swWX",
    "outputId": "48d0d79c-de14-4c02-9236-bbb45a0e965f"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/ipykernel_launcher.py:23: UserWarning: Matplotlib is currently using module://ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x144 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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T3w4XPZVPLm1ga9qzR8znC0qTkLLBp5pUWvrujHe/8iUCJWFIzOpd/OqQqikJCLO9XW586tOUlabvO8qdXVQS2uNHXH/pVazk8OWDu++y98orrLtTBudR6w1LtcdisUthNUKi265ZLBs26w0+nCfMjsGSJEw31A/L+bFKpHG2CCl7W0WTfI8tC+Z7u/jYIUE4vHubbnWfg9c/i57NWa0fMxQNQQtJK44P76JSYrbYJdmI1QWihKK8RLtasz4+yR5Y1DRKHwsXimskp3IoZdCiUUpRNrNstBBQWtOLxvUDItDM98aCoYEYPW5oCT7mSMwncPQ+HoPn3B0m+cLULHawRYUPAzEEtLF5oqkxhBUjadS6iSF7T7QtIAoxJFLylE1BTAMi2RsTfcJWWbtH6YIUEmePNnSnHfVyxmJvji0hxgFTDJAMxAFI4wkAIUWCC4jK8ecU82tKKwg5NBZjwPsBEaGsG4LrqRdLNqfHkCZPzzflPJ6UEkSf8wCUZ2dnj9T1lGrD/qvX2L8yx0dPDCDSsN2seeuLf5/l1X8aVITS0MWeoLIu09CfUJkdFIKKjma+R4yJdrOm74dvqOqZzNEPz7lJmk3GiKSINgbKAm0t8919rIokM8e5gl//4lcQpWl2X+HytWtYEk1VM3SO9XpD261ZHOxRzQ3EDcbk4gSTIvsvXWX7+B1UPadYXiakSJ8cVAYhsHfpMv3ZOoeTVYFrVxBzBWczm9O2W9zQQ1IgCsRMJezfFuc3xJjDgSRskVjszijtAWGIbI5XJFVwfO9trERufOp78VoTQsT1PVUxwxiL6zq0LUhhoO9PEXXuLS/xKBa7BxhbcPb4McFHzvWbpgDXd5I42rR5SWAKQ9nMwSXcZkN7ekizXOYKaUkYa9GmwHtHtz7F9S0gVIsl9WKXbrPBe8835Fim8C2+/9nh4/PwjLHCoqpJwNC3KKMJ3mFMTUqJFH2+XiVLcongPCkFtDUYLXiXJ5f3lsXBZYZ+g+sHbFVgy9koXmZpVxsO79xGqZKrr79ONW9IaYv3a1LscX2Pkjyg2tpchh48Ipqh72kWO0A2blKEmAJET4gebQuKevbEKyUCtiwo65q+3eZS+5T1fSZGZFx9j+46LaC1YrF3QKEFJSX9+pByXtPFNV3XYWxJVUFTCAdXL7G+f8TBSy9T6J5u6IgISQzdxkHbYpUm9C3RlpSzJdEXKGXoep/HESY79NtCkQU2gRQxWqiqCk9gPt8h6QWt63j09bc4Ozrhxue+l8XeDsfvfhV/9hik4Otf/SrNwT7V3g5us6Fc3ESbyPZoQ1nUCIrZbIZEx7VPfYbbX/0Kpw/OePRwhXmwZufSPhITJ+1JzvOyJxRW08zmhBDBlBRlTSWRGAe8P9cBYgybPFN9C59RzidFRCR7eWxdMp81GBQqCq71rB4cMrjI4spVqlpIRPwQwFYYqWiKGc60dOstezdfo+9XDJsjRIHWBdbOCD7Snh1jK8ve1Ssc3n1ETOk8pXPiO0ZCKYXSBm2LnKoRA8YWRGsIPuDDQNPsQFa/Yug7hICxiqoZvTwhsjk5Qo1RlHK2ZOhz/uQnZfg+FoMnjSt7W9YUdfNe1ZXWT0rLRdRoYDgIZKM0Sh6oFCkKw+bwGNcPtKszmmUD5EETPLaw+CHy6N23OTs8YefgJvVcU8w3xLTF9VmLR9SMFBwohYghjV4jEYOxir5tCT6Q83jcqBFkKIoKU5ZZxTlFRKmxDDP/wma5CwjdZv1EGHFiJMmTC5pSoBXUzQyjCiQprFYcPryD1Du0YaDrA7PC4FOPEXjlzd/FV37p8+wvEvOlxhYlXbSEKHg9RyWhKCtct6WsKny3Ae+QCLP5km67wnnHxWyUT8oEfXq8dyM01lA3M6q65vTRIdY2nByveXDrbS5du8nrV9/AnR5zcu82hY3YUiG1ZfGpG2gjFJWi2Wl4dOs3mNUNdVljqdDK4dsOpYXDo0eonQPmBw1deYdrl6+hhhYRMNUV1puO1emKerGDH1rODh/T7F9DFxElidlyh6Fz9O1ATIlIRE2D/Fvy/rlQNQ1FVdKdeQ4fPwTvme/uc+NTnyYp6KOjrEpwW5J39Gcr/OqUUC4QF4idw607xFjE1EAgegFjGLozwCOmRHTJwc3XuP+1r2QPv77oVfygvYRp1v720MailKC0ziklyjyRE7B1RSEV3vc8uvt1Zjt7aKOwhUAyBO8RPEppjGjq+RJTVAxlRbtZo22V9e/c8LR/5ofi4/HwSEIZja3L0SuiRst+VDaOLhs/fkBIaFGE5NEGUAprGzaHLe1Ji4ozzu6fsn78deplzWxnjlIl7fGW08f38a7l+mtvIALaRoLPiXIxxrHlRHbPhRgRpXNLiVE/IviIQrM9OaOoZyhjUWpUgZa8razSPE5LgZAEJZqUBFsvGAZP9GGamhcJCiUgEmlmNYW14AKDc4hWBG3xVuO9p1AFzsK2O6OwJSkkbGOZHVziC//ol3jjc2+y//I1hnjGkCL1Yp9+dUYfE9FoooScjeAD891d+uGU+dww9IZt6whixqqDT4YL9ukgpNggaoWtHcY2UNb0Erh19yF961leWvDm930/3ckJj97+KpUUvPzZz1JdKnCyZbPa0h1t0ViCa6nLgiok1LqlGiw+bvBWk0zCiWMbPF4qxK2RfsVOcQOrLJtuRdAabM9ip2Jz8pi9yzep5zucPHqXrn/ElZsvY/Yusd20HN+5S+8DUampSutDMYaVSJRlQ1XNIAROH99m7+ormMqABFq9AhUY+kjfr6nnFbbRlLVl4ws23YDZuc7uInD41pe5dPMlnIkMKaJRuO6Y0pA9s2hC3FLXBbs7r3D/q19g7+Yejkgiy4vIeQsfOc+NlByynK6s35wLaXd5HZ7QxmJIWG1yRMMUubAjBmL0FIUlJY/W0Mz3WR9tqHdKihpS7zGiEQy+C/jks/K56akbg1YNm9MVVb1LgJxa8gH78izxMRk8UDSzfKPJMsgQw1jdlBPmghs4b+8AiZTG0jiliBFOHtyjWlr2rl/l+L7m+P4hJw82HN4+QVRPPbPsXrnGbPcmwXd436LNjOgTKWmCD2idQ03Be5QqcrllzLlDQ9fhhx5jK5SQVWFVIoQ+R6dcQhlDCnlIRbKKrNLmSWqKaEXZzGlXZ08ScycACYhKlKVltlyiUyIqj5OEGIt3nnqxz+roMVduvs7QOZJSxB4Slnd+/fNQzvjM7/0R7nz+l3l0/z4Hn3mNYqehtiWhDYiUKG3Zrk4oyhmmKAjekWJ21dfNjEjLttuO2klTyPGbk9B6hcKgZJ/EmigbHn79BNyW7/+hH2K2s8Pjd75M8gM3P32T2DlOj2+zDRVdv2a2vIweAnaI7NVXSDPNmT8kmpJe5b5ZbdfivSKYAnSBtFtKY1G6pGp28O2Kk3u3qIsFkjRFXdCtV2zOHjHfO2DvyhVi8Gw7OPrSr+O2LU2xRCeNGGFK5PkwBESgahYURUkYPIe33+byK29QLZd02zOUAmMsKWmGsEGUxXuHrQqMKTBNhUsDmJ6ybth75WXasxPm12/Q4en7NaBww5bSzpABPIJLW/YuX+XRVwOV2SX6UwIOwX7Afk5j+VvzjcdIAFsUGK2yhweIzo2fHCMYfsCUdqzEciitaNcrjJ1RVHMUmuAjoj3JeUgRZRXDsEG0YbazQ7/ZUs+WDCIMQ/cBe/Hs8LEYPEXVYIsS13fZrTZ6VEQpRAmu77OBQc4GJ6Ssauw9ZVGzfvQIW1j2rtwEJexevYYpa/rtGojMFkuqugaJRD/kGyyJ4ALK1CgRfAwkxnYQyQAakqZvO4Z2i7EFZdNgCktMAe+2mLJA1Bi+imlUV87GjrGjp4CYDShtISXKpiHFQL/eME3SjKgebXNFhhZIPgABhSH0HqUN1XyX1eFjVoeH1HsNSIEKltXRCbqa0VzaR5WOT/++H+bel7/C1/7Jr/Hy9343s8sFTT0n6JLo+twgNkVSSgQv9JsBWwgp9pSlAV2y3W5JqeRZm4zPDgkjW4xZolQNBtYnpxzfeczv/uHfw2KpePjuV0ibLZdefpmkeig08UzTnXQgJVF5mqpgf34AHrahJ4jCl5rT7RqrQc8remfYbjp2ZzMa3TGzFq7e5NZbv87s0lVo9jl9eEQ9n4OJzHeXnB0+Rum9XNYQNU4stlnSFAsKn4jJ06XAJ8PJ/jRJiESstVRlSQyRo7u32L/+GuWsQemEIiEBUufRymCSxpQl2/YE57fEekkqLISeZLb4QqP353SPH2COVhTzOdo2BAKtG+jdQEFCkiESoTjixqde59aXv87L3/ddnK1uEdOo1wXIeTh8qrz7ELxXjaW0QYkQg6Pzubm2FAYJo+yLKKLVIBAjDEOPKUrq3ToXi5wckWZCs9xDFYk0BGxhISb6bpUjKEajS4WNlpQC9XxB2iSGvuO9YOmzNWbfcYNHaYMpylwtMwbVcym4EL0b20T0aD3Pzh9t6LszCt2gTUnwkW6zYrk8oJ4v2W5P8a7FWCj2Z4Anhcjq8GjcdrZCvR9QErBFDl3ImDR9brz4MOD6jhgcZbPAFOW4x7nnT7vdIEZIyUMAJSWIIoWcuAyQYuCJiAxx7BuUKOoGt23fpwj7ApKy7pKt4eDaVY7efovj2y27l67jBocpctL60cM7eNdz9eU38Nst28eHVIslZ4eHKFNx8PIrdP6EbfsOsZxz47veoNjb49aX/z9WX7/D1Zuv01yeEdQGXeWEcmUsq5NDmt1LFMbiXQcEmlmNG3qGYbw4TMnlF5Cc9CtCVe5iyoSqAsOww70vfZnXPvNZ6iLRPT5m/fCI5dU3iKHInk9xVPOCqjKsDg/xXU+1qFgNW7yLbLo1joSp5uhkCXGgdx1tZ3CblgjsHeyBH9i6gXboOb39Lsv9a8zskvXRXYrmCvViSbs+Ybs6pFnuE31LPxwhkiisYmdW0+xd4qzvuXv3EGBqQ/E+nrSAiJF6tqBpZqgEj26/w8GNm6iypN2eIptI8h5jSmL0xOTy9U8JxmhQgneOFLLWVQoDSitCH1ifHaOk4PTBLRbLJYuXXqHYnTFEj+u3xEFQwRPp2Ll+iaP7Z2wPD6mXM9ZtP8oLjPMzTXP0w5A1dnKVlbUFRmdPWds7Btdj9JjLIwatDFqNxUPaYKsGtBAZsLpmvnuF9dFDQDBNQxJFURUkNyAyZ+hbgvcYa3H9mt4Jy4Or2LIAlei77ShF8myN3XfM4Mn9VISqmaOMJpHjiTEElNLZWEhgipKhXQNCDJ4sepNQhUXrhqO7t5gtD0jB4fuH2CKgVUF/1tH1kRSynL02iqHbUtYztC0wIeD6NhtTY9gk+AFtLM71FM0cW1qUrkaxwUCMiRgKSDqXv0dANCkFYsquX2WyJyqEUSsohDHpOhtVpGz5ls2cdn3Gi+rlSaNRK0A5q6iaivl8D5tKVo+POD1+QFEatDHM9vdpdl+hLGrscod7v/EbPHz3i1x57XVmewu8O0NiRKLC9S2b/jbFrOazP/TPcvbObd754ufZuXaZ5ZUDirrEhY6h3bDY3ydEn2UKOo+1FUO7pShqfIgE5xB1oV3Fi865YTCWdpezAsqKr/3q57n20mtcv7HEDQP37zxAz5c8PrxNOIZh6JjPl+zvX6G0UC8qnB84Ojqm67eosmQYehBN6ROlrthsB/R8hhl6Kiss6gplC7Z+YItnceUl7r/9VSQGmr0dQlhy8vAhl195lcX+ZbZnp6wOD6kWOxSqRYlQG81yb5et27Bt16OMRJoajr6fRBaIRHLI3wuHd95m/9JVyp057bDJ4nOmQnRBjB5jiyzP4QWlhNlilxgDhZ3hxYGvGLZbBrdm8/ghzWLJqz/4e9geP6a/f4/7v/4FmoOrzG5cJ80Epzpk0KzXLWV5ykvf8xpv/b+/zM0rP0AfHmQFeznP2TlXyXsxr6UfjjTmrRrq2YIwDHjXYYoCow3BOYbBYcsKHwLapizMaxyiDURDDB4fOvwwYKRgtrPH5uiIeHqGjwFthb3LV9GUGPI5JAHKssIR6bdn6KKkqOus2dNn2ZdnycvzHTN4RCTnuBiDNhrn+ie9VbJdICARrQ1C7miuRg+QsQWiNKeP748N1XOOz8ndY1ZkgrIAACAASURBVExV47o1fhio5w22yitM53LlVb0oxjJzwZazbD8pNZa9J5RWOO+eqPDmirHcJT04j0+aGEGJxXUDthrjyQmyaJ4i+AFlTPZYCeM2cmVW8A4Rja2q3Ofrgl7Bi8R577NcFaAJziNJc/rgIc1yn099/+8lDGeE0OI1xNTjBg9RU1RLXvncq3T9XZAWoiCDptRX0Lak3zygT0cslpErn77C/uU9Th7c58HbX+Hm574LEcXy0hX6oWPYbhi6gLGG5LOxHJNgC8ZzYipdPkfGFg1aK8Q61mfCvbffomqEVz+3j7Rn3L39kPrKdVSZqItdVmdrjFsyHG1xrUPLQJQtQ4oMGMr5JbSKFPWStmtJtqB1DlUuacodhrPb7MwaqtJwenbKOnREY5hpw9Xrr5FChx9OEZOw5ZxHt97h4Np1msUem9MNp/fvs3f5IJ9n0bA+2XLarWhTZLF3ia7d0G83T/vQPnXe33LuvMlnCuDaAa0KmuUOPg74uEGJwtoZEU/EESRQzGdIN+CHDqsrxCf69Qmbh0doVebGy9t7RN9x+c03uffgK1QHB5Tly1zfu8qdX/0nbI8O2f/MmyRJbLsVZbPH4DcUS0Wzu+To7iP2PnWN4we3s8LHGMqalLR+a7Qt3muhBFkzbugxxqJF4X0W+RWjcdGji4QkR6LA2Abvc8Ws1mCUgsGzs38JY2Y4n+jaQ/rTU7ZnW4pqSUyeQi+pqyUxrp8MTwo+98aMieCerbrYj9jgOb955FVzUdUE36HKClTMFqHKoawUQ861kYqUssZO2RQgDuUqVveOcdsNzWI3ixDWFWerU4ouUM+XFMbk3jljDNIP+SDH5JA4CgAqsnGiLcYoUBrvs6JzFjlMKMmNSmMIo4ZHJAZHij3GzHFdhzI6N0RUZGXoJKMbV6M1qKSzZmjMJbJKCWhFuZiNgoQA5z1Hnl/UqDCeJOveNlWNFcX23UMevnuWVx+X91gc7OPjGdvtGcoUKJ01BRHFvXe+ztVX38CYgD+2nN47Yb57kCvqBIgDgx+wzRy33mAKSBUsX7/Kpj/j/tu3ufb6GwztJrcZ8RpdFrjtBl1agkSUMRQpQaHoujjmCoyVdS+YpEAiIUllZV0iSidMIRTVAbe+8HnmtuDT3/tPsT66y+roiMWVq5Q7DWHowAcWSiGFRl09YH1yhCn3cF4h2mKLhEo9pS3xQQgoxHlEIrW2lEPPbLGHKS0uRk5PjlBNhSZgTESMxiuN81uCidjdOXIWGM7WLA4uoS4LVg8UG8fOqy/z+PG7dFiirtCDR/yGel7QuxXeByQpFOqFFLlLT4SoIiIBW2jqecNsucvm6AhqxdY5MIoULKIcSQ1EhKLcZX3/Ae7BQ/qzE4REOZsTSZiioprvUu0uKXdmuH7L9vSQZBPD6TF4j9m7TFwoZt/zadJpx+o37hPxLN64glnMaVuHT4Ybb36OL/ydX+Ty6y9Tzxo26xMS9Zi/M3Vg/yDSKGIkSqO0ICnmAptgsmNMh/HCnENdKcWc4+h6un5LWRXUswJjS/ou4gehKhqCP4Fqi7VzhtYx+MBsWaC1pphpBhcglmxPt9Q7O1SzGUO7JXRbjNWIeGxj2K57nI8ksVlg8kl17NMJdX30Hp6xgd95EnC3XaOjIQaH1jaHtYYBFxwxDZAErUtcN1BUWcW16xyrR4/Yv3IVpTw3PvNdrNaHiEoUdoao7BGKMeGGkG+GukTplMsYU8L1PaIsqigIPivu6iKLHsaUUDH3XIqjuzvFOFZc5RUuYjG2QNuCbnOGMRXnZZLKjKujFLMWrQ+jjZdl7RNxbHNhc4zT5d8pL0Szn6zUGnzP+mhFXVTUzRxtLcvr11itHrBaP6Qsy7ECLxL7bKyujx5j6xmogOhEPV8SXE6Y3b18FZFI365zZYgqiM7h00CQiLaGg5df5/jWbR7ffodrb75KTBFjCqwpkJRblZjC4PyAHb2IrvfEJ13YX0Bvz3hS5qatgraWZrHLw3ffZjaf8+qnP8ujd7+CKMP+zTfpwoboI0UxZ3t6hCRNipEgAU9ivWmzTkfXg1J03ZZh6CjLJYv5LkYJ0a3RozSAqkqiCNvVGSBYZVDnuXLG4NY9xmiUVni3Zb6zx3ByQnADPmxodpbI6UC72eAC6MKC8yjl8L5DxYHdxQ4nR4dEgZgimhfLqAVym4iUi8KNNdSzBq0F327ozo6pmj10UdIPG2LwmFlDu23ZKfdQG0fYbNl5+Q1m164iIYx5W5Jb+LiBLqzpT8+o5wuwgi4LrOvYPLhP7AbK3T2qRY0qGloHKgnrB49YGEVVznBdR1HUXHntNQ5v3Wb35T2c7+i781Y0kamy8jcjMauLFUWJMo4Uc4m5qILBBULKMi+mLAmuBzEYU1CWFVpd5vj+bU4f3SWGgB+GnNdVX2bn4BLFvIFk0TaiOSGSED9DRDHbK9ienbFzbYfVySFVfQnEMAxbinon55nHQFVXhE3LxWxWGeMrT4Pv0BmUc3dsUVGUFb53KDH5pp94YmVqZYk+dx+PIZGCwvewevyQejEjpJ6rn/oUIW1IacPQnj4JkYBQjq0k/NAjShO8z50LYhr/DpCy9yaGrM2Sn4cn20kxjmEoQZucYJ1bR2Q1SqU1tpoxbAdAj2GaBBIAl70D6r0eWyJj/pLKVWjlbP7CrCjzIjICjqqyXHn1dXauXsc0QrQtZ2d3QCdCjDgXcH0PMSIYggu02y31zi5D14+lkIrZ7i6z3T2OHt6i26zRusiduHWBNeU45mOlX6FZHOwRfMfQDhTlAqWERMC5HmUsWhcQwfc9KgR25gusjA3bXsQLaowQHVVTYqxGa0N7tiIOG66/8QbvfOUfU+3tsXPjJdabI7arM8KQWJ+t6HpP5yOtD/SioJmzaVse3r3F6uSE7ekaMzvA64Ku3RKHFu17aqNRRtOrwOnqkM3mFO8HyqqmbuaYYpS171r6vidhMGKpjM36SUrYrk5QCFESflZw5/Y7uEERh4CtBLEduiyIbUsdFQvboFIcV8QvItloUBq01VkpPiTa4zV1uUdyIeuhpYGqqZGkMapm8/gxp/dv0ewtCJXH1ZGt7mh1z1n3mJ6WWEQiIacmuNzDLvlIUc4oqzmp96TVmjIlRA/EXZC9klmzx/reQ9QAse/xYcvBK69w/62vZQXtZo5IgDSQO62/qGP3jZwXrAmgESwamwSCQyQQwgbv1znfOyRENMEPBO9zJEMghMD9d97BVJeZ7b7MztU3uPGZ38mNz30/5WzJyYNj3vn81zh94FGypJrV4/8rGLrA+viIoioI9DT7u2xXZ/iQQJe4AElXqKLGFhXaFM/MPfAjvsK/590RlWOGtmxIMVGUs9yVNWVBKa0VYwe5XOKdAt16xdHdezSLJbuXL9HsLvCxZbs5ot+cAGmsrArYssyTNoY8oC4bO77P3pQUcrJicJ4UE9FHgo/EEHPjNJNdbNraMbkxe2Vi8Pi+RxtD8A7XtyilUdriB4coMy6KY/YQeUcM4T157TFRN7gcLzW2HMUNn39pnjhKZFsDRamQ5Gi3Z7jU57BEcmPFjDBbXKJu5lTNnLKa0642zHYOMFWJaMswtoQQDbYuqOZLVieH9G2LSgodNRIFGXUiQgh439LsNFx747M8ePttJBi0UiCgqwpVFLh+IPpslBZaUWtNSXZMvphO84RSCa0TRWUhRR6+/Ru88uZ38eDrX2B5+RpBaQ6PHpCsAmVYn56wOT3D+0g/DPgIPkZ88JTzJcsrN9i58hJFM6fvB7StIUUMCaMVoR/w3tP2W3z0qMJSL3YRUQxdi+s7klYEUbTbDSSN8pFSIPmOcjHD+Z7C1sSYWA0tiyvXkRhRKWvGIILWiqqqKLShrupxfj7t4/2UEHmvDU5TZwE6CrbrLeV8N3vQ+jVGKwyaJlj6R4e04ineuElaFOgwYIJDSUIrMEYjKZCGDi0KrQpSgKKYUZQzJAnGlOxdfgkjms3RfbabI4r9Gd7mRUhVzmEIECLrs8eE5KiahtxzcUlZVrnv3ovoff1mpPc8JIJQNwuKosbaBmXKJ5p2xlqKao4f8gK+bOZUswUxRo7v3WK+v8tsr0GVHl04Amf4eEKz57n0asHL3/Ma3eaI+2+9hda7qKIk6Q22EgrbMLQQ4wLXZQfH5uQR873LbFcrnI+5MMS70bP0ZIefKh/9knYcib7d0G/XuL5FkhBdXgH4oUMJFIXFGkNVF5SVoawM3foELZprr75B8BuWly8zDB3taoNQYm1N166zoRECQ7sdQ1EaUXpMHFZjcrJB0NiyRimLKUqUMrmNhFKjKF14YswopbKx4waU1mOTUJe7xIbzEuqO4HpSDo4imBySCT57ioIfjZ8LVSEpl6m/ECgFKjLbmaN1ztFCEmW1pKx2kGRQGApTIz6OFf0RpTTeeVCKEAacG3A+0rZr2vaYtj2l2d1nefk63jkOb79Ne3KMSiqPnS4IgwNxFJUhJc987xpH9+5SViVuaPF+yD1jeofrOohQKI3qt9S2yCGWpz0bnwJq7GsmeOY7OxADy/0bdKsTqnqGbXbYbDukaAgILgygBdFCDANWm1yx0W8hOKLriGEghA7Rieh6Kluws9yhsAY/DDg027aFGCmKiugD3WYFJJQI2ti8dNIa5wPtakNla0qlKMqCdnuGrRuiG5Ck6fqeFFp2d2v6s0e0py1FeYmyKLFNzdZtWG2OKOryBQxmZVLMsiC6yFWnwXuGtkfP5/R06FmBG7Y5zykYVvfvsXv5CjuvvEIvjt51+M0G40D7hHIRFSB2AwqVK79CJI6aZJKEopyhRBOCJ2kFtsB5j28HirqmPFhQL5cc372DVTXVbDdX6KrI9vQhYejy9Vv0VJp+ARHFeXaE8wOd7xmiI8YKxZKqOSCNKRui8nxSWgMJPwwc3X2X2e4+s0WNUluIK0gbkt+iCYgeUMWWcu648vpVlFbc+tJbdOtAUgmtDUVRk6LQ9x5EYcSz3N0j9Gv2r91gdfTwidZeImGLaiybl6cqE/GRn0XaWIqqGTuO5xuIUgbXtWzPTojej16erKY8dCti7Jjv7ZCS4/LN13HdGvAMQ5s97kGjpKGsd5jvHjzRzLFlNZaE5zJypU3+TlGIyo3SSEJRz9DajlVjNntrXO7UnlWX1XvigiGLC9qiwhbVkxL6GDtEJfo25zBEL6Q4Vp2p9/49rwgDRpdOGt16H1+f1qdJUVZcufkazXyG69d4P+A6j8QCnMJvexgC3ekxw+YU122JzhMGT9UsxrwqiD7mY0lOAhcRXN9RlA37V18h9I6TB/dyaEpyKFJE8L7FFgX7116jXZ1lraexdUmIOXxaVjPKukGLUGjDrJlTVvXTPnRPhQTU8xw6UBqO799htjyg32y49tp3M/QeHxSDh6536KIAlT0F1hisUpTaYFOiFLAKqqpEG8FWlsJAkSK1tRADqm7oQkJ0yaxeUJgy5xjYIhcPpEiMnmHocMFTznbyXFbZsJIUc9fm5S7daoWKGoOlrhSKNZevX2N1vKbfgPiIFIZWBmJpskRGOG9V8GIhIvkYE8deSSXteoVdzhnUAJXCNk2upLz/CL27RJYV0m0pOo92ES/Qh6xLlhcoBhcjfcy5Iv12w7DZsj09oVuvn4S3IhE9myHNjHpxgDvdEtqO6vIuDgeJXB6PIYTAwfWr9NsTtNFYW+I6h+TRf9qH8ZlARml/pTVRQduvOV0d8vDOfc4ebYnBUM33ABkX9Dndo2+3HN2/xc7l61SzBcF1OckYg1UNVi2IvSG2Mwj74z2uZ3GwD9Fw5zfe5dG7J5DmBB8xRSTER3TtPQg9u/t7hG6Nkshyb49udUxRjRGeqn6SIytPUfvsI70LJ8BUFTKqKefSbY1WuTlnrs3vIZZ4IlFLFveTAY8mClSV5fTwHdAG13Y5cVgU0Q0UtskpsSmQogeVRQxj6klKiGLRtiD63FXdaoshJ2OFFBCt0dbivUcX1ZPEqpyslTvKngsJ+qHL/b2iR1ReYSgspmgYNj31bDd3cjc6Czal7M3ISdB6zLPLSdRKKYrC0LkWPlA2/ZOPkFd+xmkO376TS/wHn5uuKghD1oT4/8l7r167sixL71t+733M9WSQwXAZaVCVKqOqLFWjgRb0Iujn6kFvemtIDy0IEEqtRGVWmsgMR3d53Tlnu2X1sPa9EdklQAVEmiZzAUSQiAiS52yz5ppzjG9IpWtIrJSI4jDtmvmwZ7s9QuVMChkrJNIqErHqo4RkngdkUztqUxo5efYB0/6W/uYNq1OLbVtCgsl7jNVE/5rjJ495/flLTj58SsQT5hFtDJ3eEFNgVnVTpN/jrGEfByh2SSSoQt7yEOX8Lr1s7+NbCtJ0aFULirv9SB8Uze6Gp5/+gDevnxPHiTIHdlcDUUiOj+qYwfvE2EeUCHTdUjxqg9QNOSQaUWisYl5vGPxEyRqlNCVGitGInJAUigDVWHLJ+HnEF0hFEXNAiYQwgpBr8UOIlIUjIrVAmDW+79lah8AxxapP2Fyc0t+85Kh9TBwDTlqUiRgJRhVCzuS82PAfWC/LRvIOrVK+sQRLAZvjLZlDNQsUSRAjuAS5oAqIIgnjgG4tamWZph0NBmcavJAMYURajVSFEDxKKqQ0xDCTZo+zDTll9pev6bZnzLueYXdLs9nQnp7QnBwx+5HN4/cYb98wXF8hU8KmxOT3SLGl1S2b83Ne/PY/c/70+xQ5VQo03ybxlP/iWv15dX9yrow7ax3aCLSWaKuJpwo/JS5fvaz7jyh1n8wzxjWkUjDNFtW0lDzW0NbSEPMMUhHmqe6pMjOFjJwKIgcogfP3j3mkzrl5ec0Xv/wFT3/0Kc6CmwUpQJgzWUy0J8fcXH7O8fljih/ZX12zWp3inMFPkZglJRsQ4U/y3f1+2w5S1CruPjNLCFKKaF1TV5UxRO+ZxwkK2OMjSjpQRCFkTyHjWoUyGrc5Zur3dR55r/WxtSVeoVmFnKowTgIxBiiFeRqhgBTV1RGmjFAK07b4MENOFAF66d6kUIsxACkV8zQuXSKWmyUhjX4Yt0hhcG1LjFNVxku5iHUFmYJauhHkglBiafUmjK1grndZx6MEEBNkRbe9YNhdYdsWax397RU5enKueillLEJbpuGAtZYUPMPtNapxi7hYUYREakUKvpYcJYMAqQTjtMe0HW06YX/9inZ7il41FA0hTIR54Pz97/OLr/4PNjEhjERrTaMdCkXKgawkSUqMrfwKawzBf6MV+CZ78r8ejsTvZ5WHJkfOgXHX07YtL77+CrSjPVpx+epzBIXjkzNiCDThiMM8M/Q7/OSRpsW4NUaDVqBzwdqWEDOpFIosZJmQ0jLvd2QaZF7GySGglWQaB2KYUdZgmqbysHJCKUvOAWMVyupKfD09JxZJTIksKgq/aI0fe1q7xvuIjyBFotseIXJkHiZst0KgUGik1LVjG1OlpsM9LaIaKt6xgqfeslUrKRPE3QHTKpRq6e8GTrcf0LotftpjZcM4XDKPPavTC0II5BRJSkKGVDIxRqZ+j1V26TJUl6pCoFdd5cAgaUpCGotUhpPtFlEy1y++wu5v6E7P0FaA1GQh2D77gDCOaKMRtiFkQbdpGO56cgiUUDBWkIVlmvyDWPe/+JB/dktQ98PkPSXVOCYlcrWZP31GCnGxcEW0VChlmP1MjDNiQROAYh6HGqeUE4W6r4YwItAYHHGaObo4x8cd2gnOnz1CvrS8+tUv+fBHP0DbNTkd0O1MFomUE9uz9xl3PZuTZ9y8el73ypXDmLrf3k9G/hTr9/onK2VqV6Tkh3GWkJKUAjnVgkQv6eQ5R6Z9j1YNUlhyiLSrDTmNpBRISyzD/SsoRF8LGH8gJ784ogzJF8iaNCeijyip0EbRrlc0R1toLLJtKEo+5IsoKSh4gt8jVUbIhLES4zQlR5rVCm3q3FMquXRuPFKz6FIyOfvlBpGV0JwzOaba6i0FISJCpMWtpVGqRZl3WctTsG2D7Ry5BPw8ME8DUqnKUsoJP/XV9r98t4WCn4falVtatLXrUB9ASiF5X198MeG0w0mDQiKFwoeJIAurswvGw+0y8lphdItRDbkUjp8948Xnv8CaFqdbiIWyOPUkknnq0es109SjhUSWxENS83L3iXcsdbsskR9CCFYbC9rw8stLxt1Mt15h1pru5Bi3XjFOd9hVg3ESowrdyQVZaaZxj1FgSqazrgbw5kRIHh9GitEEIZnmqV7HEEgxEP1MSoEiFZgGtz5G24YSPVZJVq3leOs43lhakTg/PWfVdMxjT3ENU5iZ55FUEkVCJJG0JJaAcVUX6PsD0Vdb/DwOlMU9RMqs1ieLngHe/c1SQKkax6OzC6xtOFxeMlzeMb/pafOKdDVR9pn+1RXzYWB1dIbtOrQ0aCxxjsSQCTEjdQtCEfwMCHLKRF8F6EIpfJyIxWPWDXplUa0iq0DSiZP336ekxHB9Q+kDjdsiTcPV4Rr76cd0zRbrBVFJhMu02wuESMyHEe2gXW8RsnYsqmRXLj/e9Wv4r5cQBaklYRrQtqkThQwlJGQOyNIjyh2y3OFswKhIiQNxumO96ZgP14hcSLNHGVtHYyku8F9F1x3RNBX/oltLkdX1PM8HQrjjydMPOV6d8dt/+r/5/NefMyVdzTxSMg/9Au7V7K8v6Y62y/5fNbxayT+pAP27FzzfIn4rrRFCLrbvylgBsRQOC+dEFJTWdJsjop/ob28pSTLcHbCuI84DKc6M/Q6hNcoYbLdG2yo+LWS0dYsIigcnlhSKttvg2hVNs4KSKGSktVWZKQTG1RgJ4xw51VgBIWo0hXYVoa6MRiiBVALTOEzjgILWup4uVD1iaGPqS3VJSs9p+ayyfgdS3VvYxSKSjihVYykevrd3YT0ItAWmsQTfI7UgzD1CwHjYc/Pqa1ZHZxxdPEUoVU+cUhL8jHYtQquFk+QQi9ZpngZgGSblAjEhi0AWUQugkokxII2mSMHx46ccbt6wv3yNEhqRFMPdNcdPn0DJvPniN2jVkHMmxBkh5QN9NKhCTJHOtWgygkwR+R0dZ9UlEDVzxyrGaWb0cP70Y84eX5BFZpx6+n5PLImhv0WUiKEQ56F2YJ0h9DfIkvDjyC7M3KaZPo4UUdBFoqMkzwHXrZFKYZsO23QPrsaYPMj6fGjjKt1Xa8o80CjN8fYUt3T7dNMyzGO9OjHip54iM7pryCVTcsAZiTMSFvutspaUI/vr1yitca4lzhOuXSHFfVzBO76WbnWUPWorOHr2HvaoIzIyzlfcvfqS3fPnGNOwPn206D0CUkgEEmksWQi0aSqyUVQdZMoZhERZh2k6RBGoJCiTxyBxUqKX65JlIZfM+vgMmQXXv/2M4c0lnWoRYekIhgS3B1TIJOnRtuFwfYkxLaYxZBGRSi7Rd/fX7b7o+fNa1W1nkKrmoUlpYDkE5ugpaargTjzJD6Qw09++oduuKMWjjSX5jNKuYlpydRxLVSUo2UdkUaQwUmQiExd3siDnmeRHNptTPvrLn1CE4vlvvuTqyx05dHTbC4TwNFtBiG8oIpKXJAJtHK5tkX9CNMR3vlvKAz64YJq2zo0F9RSXUhX8xup0SimgjCYnj20ajs7OyNFz+/I5465HYIhzwrgG03RVnCxl3fxEpQ5oXYuWadjT373hcPuaw+1LcpwqrExV3o8UhhIyugi01HXThIcgU20sUuq60WpbrX6l4LpVFc7mqhOSSqG1ocQCEUQSaGlQwlBiJsyeFDIpVK6Fn2b8NDEPI9MwMI99zfSKc81tql/VOxVoWHKuXRstkEZWsbkoZDLDYcfu6hWmaelvr4jzhF/QAjEGms0WhEAajTQGBMzzWFkeOaGkxBiH1ZaSEnGBSMbgKTlVsKAx5Bw5efyMab9n/+aK9fqMMA641vLJj3/CvDtUTdFqQ5SFImVN/p1HPFVTZIqgMabi1kt+GGm9ax2euqrIP/QTRbb4nHj0wXtkf8vzz37F1as3zFNgnGZiyggkBklnHY2Czarh5PwRs58ZQiJKSyoglKJpWpRQSAxNd7TYYbdLpt2MsQ5KpHEKYxRSClIq7G739PuJFDVhzKS5cPvmErPeEkomFwEZjDJYbVASVusj0qFn03Q4Caokmm6F69aENHL06BGbs1P621fcvPocSsS2q2rTlu/+ZimErGM8Uh0drlYEIusnF5hTx9kHTzl9+gRUAV3BjDnGCk/VgBFop7G2cpBEyvh5rnmFrq3ZgkKSfESLBhEF480d092O6e6WeX+gv7llHga0tpw8esL50w8wUrN//gI7A71Hnp6yu75mW0w9fJwccfvqNeuTE0oBqTPa6ofD1Tc/3v1r+LurdncQ5QGjklOuwm5hlsiQXN3IwpGCZjxM2NWWAsQcyQUKlhhSFbIXFjNPTU+XSOIwYpoGVGHo7/DzhMRQEgxTz5QPSJt4/P4FH33/h6RQePmbXzHu99i2Q5uakehDj2kcU98jhCD5Ea3/dO/T76jhEQ+5i0rbqolJYVFh11O8WGIbqsBX45qOMI54P9Bs1tgnTxhuDkzTLePdgY1do21XiS4L56a6nxTBT1X0PIy4bs3q5BSAHANhqkVF8jOiSJQyhL7Ohouqyb7Bz6AUQonl7yiXjRXmsW6gQmbCNGKblpwKKYY6w54S09BjTINYLO+FzNjvMF1HkQtwsECONWxPm7a2DKV8qKTDPNffc/n+3vpTZiUt0q42SJ2Rpr78chYIpTk+fYKzhpef/Ry3WtNtTwhhZhr2KFN5KffQxprC3BDnoQrfl25hHWEJUs6kklHW1oIxF0oICNcwHK7RzYrji6f0V1dM+548B+bdDev1I47O3+fy68+5+N73kM5RQsIfdmjnKEbXwlYq2qZh9H2NHvnWtXkHrtQ3q1DHhikx7AduDzOy0Qz9V1in6I6egHTEaY9TDlCUUBAJWiPxQrpRfwAAIABJREFUyWMwlByQ7Yq7uwE9K6wsbLYrmtYxTgM+FYTSpL0n5wgI2vWWnCJGZSSB1WbD7uYGPwcyDh80fgw0yjD119ztLlk/ex9hLCJ5ZBG0q1Xt8ASPlA6TJY20iDwThaz3lAREJKaBZtWQ/JqmW1Gk5csvv0YqW7+LdzhUVCzPljaW1Geubl4sDtYVm7NH+HCJcoUoepRpKEJWZksQJFVIZIqPdN2GNI5oIVFS4kupcUAxLpyVAFmgVoasXZUDWF3jeGZPIww5eMbdLZK6Sa9PH5FRXH35GU/+5ifsbcI8uWD8+gv0j59x9sEJP//FT2lWLbd7cGsLGPw4fvMBy78S9Lzjazm0a1Mbd6qCQqVQ+DyQC6RcKu9OCEpxpFQwnSHlnljy4k6mpg6kug8JKR469cY6SqqTGOqjRK4xAuRQkLLDp0gxiSlcokKhaU+4+PgY71fc3Vyzu7zk4vH3OHr8KXe7L+g259y9eknJCqUEOd7LBf74F+87FjzfbAHauiqkUosAquSKiC8FiSHmTFn0PNZqih9IvqAbx+rRBbe3A/M0EtWaJBWybTncvMGxoUyFeb5F2nqDt+sNpmlomlXtHhVHioVpV1N+Uwi06+MaUzHUXKyUE34aaFYblFFY5wBBERBmj58GkHI5hSbSOCKkIAaPoI7hrGsq08BUt1EpuZ5qpEBZVwum5UQlpEaqSvlFSRCqWmhtpQO/7e/ZskSI1HNWRqRAmhLObZjTAWcbAFLoOf7wByACu9c35CghK6SsuPPpcIfVFkomhRlhDEZbyInkPYLKfBFKQ0povbCPloew5FIhhaIh+oC1kkfPPuHw6ooSCmnyTHrP5skFt//8nPHyhvb0jFkeIAfWRtGVjGlbnLNooVD9gVA0tSBOi6Og0r3fzlWAiMgNohiyDMQcqr48RK5e7jj64DH7JGjylnUzE3JAGocfJkzpMFpgjULmmriclu4YqbBZWzpl0KWCJ72fCCUx54giIZXAT3M9ifqI0ha1WaG1YTwM9cQ4jZwfPUFIy/XNJaX0rLdrtt0FSEmJM7ZV+CEwDQMgK9lVzKQCz7/8nJP3HlN0Yk47xmlH067x80gi41YNUiukazh97xHT3Y55nokLu0sW+fZe3t9ZC+sEVUN3BRxurjg6Oebo0fv0d7dIoUmhh1iIRKS0KDQlLiJkY4lxRtsWP/XEMWOUIocJoQTaKRCJ6ANS2SpFCJEQZ6Sl4jtiD0liVFdxESlinUElyRgmbl5dcnR2web8MTcvP8c8PuPsk495c/VPtJPGna9gcNyEN4jkENnXg6+CnBbRvfhzgBGWb34sn1fprga42qYe/GSNVBGqoJVbDvOCeRwq9FYJYvS0y0i/aTdo0+L7iJAVA3FvxImxR1mFcdXRTJaEULtIQteJTpx6mu6UlCeKTJTQk5LHuo6Tk3P8KLj6+jVxTrQna0KcGPOBttmScibmnkKoZqFSn79vNJN/2I7d78WlJRAPXQxBoeREyYW4dGdI1XsvhCRMIyV6tBDEnNndvcGuzmHdMl3ekaTEh0CzUszzyP5mh6HDrS2601i3jJKmien2jjjP1aLXtBw/vkCqRXluLMpapqlHSV2LHV9dVTkm/GG/nHYUQhmE0A/zaacrp8e4lmZ9TI6h5pOoqvmQWtdbMGWMq4LKmud1n5geqekXkkJEaEmMuRJjlebBJfOWY+6LAHLCKEOJgZhjHR0WSZwn2s2GkiWHqxcYpRBIpv1ATCPrs5q2m2OmLPeNXPgMyhhyAOMqtyHHSAgzqVTdQBZQikBqjbEOnzJy1aFEIoSJucx0Tx4xv/gS26xJBLLMnH3wMde//g1SGZqLDdObN6xWKzrbkNVcre+mAixFlotlOVIfxrcbWbcQsWr+kQg0DsiCyStWxnC0shyuntOHU7pO1ODPhZre31whj08oy4GAVDBNg0aRpr6ydlpNjgWUXm7thMi5jiVdi7EVECmlIYXI/vaaVbdCGYN2HZt2TdzvMc0G3Wq0SHSbhv3NgTTVwxLKVdGqUChjsUYz3L3k7OKUuc/cvHlNc/wY7AZBplmd4A9XxDiz2mxJKXHz8kua7TknH3zCF7/656VDWWkx5a0vekp9pxRRO9elSgu2F4/ROpNFxIcR5wRCaKQUSKHroSJXW7q6H/MbQwwBgSKFhERgbA1hFiFQUqw5SctpXSpBSjXOAzJK1D+jkMgqodcaESOiCNxqi8yZQ7+j047++XPS7gb5d/9A+8lHHF68Yv3hCacffMqw79kcHaFKIOlIs1oz7Prl8/45FDz3q35WqSTJzyilyTE+QHSV1sQwLtBbi3UtQmRMI4jeo5WGRPUrKoMUoo6n+oEwD4R1wDiHti0hRIZhZL12yGKQRT7QkovIaKnIs6cAWQnmecQoR5omlLS0nWP9yYdcP/+cdn2OJKFioPhFvKwFzjr8FPimBFkKuj8wYPL3UPBUQfA9/RFZ2541s0PXkL95RChVqctSkkNgThGRM7OIDPESbEtKEZUUbdNCzihZ2D65QOktUiVkGUFkmtWa6e6O8XBACs3qdI1bO5Qq+GmHdDAOd1i9RjpRLa4rCSuHkorsE6RuYcKUurENoF1T7bQ5I2QgihmpKkyQVG+4UiqcsFBZCDnFJXw0EXN+sKmnGEGqh1mrMpbkE8Y6JiGXccnbW/Assi0EYKzFGEcOlTZdQY5qEdQpbr76AiUs1mzxIdRU+5xQxmJsiyww3F6hZUuMgZQiKfildSuRSpJTJktBUapmlLmWNAyQCiV4hFMIrXDdhnEewTlyI/B+QkpNKhHdGI7ef8rl8894ar4HPqG3jhgj3s/IItEC2maF3w8gRe1h3VuY39pVT/xFQhETRg08e/I+a73hN7/4mmf/8Ckf/dUH/PKn/xs/+38+I+pP2QhBazXGVOfT0B/QtoFUieRNqWNG3a4oMdBPA0VAiaHq47SmaVekMEEKbLbHjPtd/ZtIqti8RMiCnD3t9hhC5e4YIXDSwDywadfc3txi18eQQLII3AXs37xitbY0JmJWDUa19EPg7nKPXa3Ic0ChMU3VEnnvUcpQQqTYjDEOn+NbXuR8ewkegpaWXyqtsI2jxGHJnSs0qw1SQkm+ZhFOE1LbavKQCh995R4pgXR1s9PSIaxDAuumYRx7iBXbIZQml/rfC6lQ1A6uyCC0IapMLDPKNZTgSXLEi8LqZEu+uuVkfcJh3rN/8wq5aSkvJGHaYR937H99yck/fI/x8x3m6QbTFMrd4d25ZP+mVXEOOUeM7SDXeKRaaBr81KN0jUsquR7OlLYIUc0ApEgKEaM6imwoHvr+DYebG06ffEC3OSNFT397XQG8STPuB9KgMFog9RK8jEUphxYSrQ0hDEgpcJtj5ilQcqDEESUirmk4enTCqy9+zoef/jWlPYfeg8xIZ0kpU7L/o086fi8dnnt0tVigfSXnuuEt9nRj3ZI7VS9ckYoiDSVIGtuSS8BaR4iZrd4QDYS053uf/pCrXc/1zS3OWFbW4oxGlMrdabfHixVektGEKZIiUAohFmQUFUgYK7LeGEOMuYpslSSLRJaQkqeoegLKJdequQS0aSiiCphlgTTNSL2A80pBmhpyCBWAqLV9cGXVl0+ptnbE0sWA6lrTpOh/H1/9n2SJ+wYVVRSpta3ul6Yh5YDSVYiaSyaHhHVbrO3IRaDbllQi+QEE6AC5jPpCLQTVUjTmhDEV4iiW6I86DpQkv0dTT+RWyIq3TwKVDTl5yjxhrWU43LHtHiGiBw3riwug8Oa3v+Zke4JpO4bgSaXgh57V6ghrLCLv7g//lHfA/lpE1SQVPMdnRzx9/ynpamC6vuXkZEUTHX/7d39LzIaf/vwKVh32eI2SCaklQmvmGJGqAWkZZ48SCWcUSghCjGAdxlpiiohQr5MxDWmuhoKm6/BzJWGHuRbGsoASSxjoHOicJYYB23V0zQpQ3FzdVGFsSGhXrdHTYYezls36nHl/IMVELgLjFMftmnE8IHKDVg5JHb9wHz0TAkqIWlD7+M3R4+2+xP9qCVGwrSP4Q+24icrk8dOIMXoZCafFJWeIc2aeR3TTIrXF+wmlq8axKEGRhjCOSK1o2i0xeUqYEULQtC0hRdLskcqhjSPFicPlK3a7O3TX8OSjH5DzREwTtiSUiHCyQSrNljP2L15w+vHHjBGm6zesP3qP65/+BmELeRZo2+BaidK35Pin/nb/uOs+rqiUetC+z39M0df9d8mpFEJSUibOI0bb2lzo98zjhB+HOpoSoK3l+PEZbiWWA3xgc7oFBM3mEbvLK9rGkcOAthIfeqbDHVqs6I6PEaqAqEWyH+a6nxPq5qAys79DGI10lqHvUbpjng4UC0opTNPhp0COeYmE+uOs717wlPvqMy9guPutsCybv6KkSN3HakclC02REolGF08jBRdHJ9CskNNI0zoaEXl8cswwTwzDjjkozHZLe9JVdop1i708VcdOEVV8lWtLVus1SrbEFCipoGxDDpnxcKDpGjLVYcWSpVWI5MWpVagWcqU0OUWUNNXqmhMkUccC9xES9/9PzggrH27KezFuShmty+IKUQhY2o/zN3lbb+FaOucooVBS13DQVDHmJWdCjMzDHTlnutUJYYndSMnXYjN+gxgP88g8HGoWmawI/LbbUGnHoiZ6l0LrVgz9AaFq6KvMpfJ0SkHOqTr69jtyDhQzE4ZD1YxcPCbGhNSKEA4cPX6CCrnCDW3dYKW2ZBExxnHz4ku0skQy6X4M9Ha3eEgkRC6YUuj0ihw1v/mXX/HV519z+tGW/U3hvP2QH/+3f8ln//y/Mu4EfVMZH41TNJs1fd8z9jdVlEohRg/OkoMnK8VqfYZSklQ887hb0poFShm8r8gHZI34EEqglEAJgVMOKQtIQUwBLTVKKEoqhBSIQiNSwVjLHANhPlD8yNnpGUjD6C1SFKTKUGaOzk9Rt57x9oaTi0dImZiHnpAyYRxZnb6H3x/Q2sI8LE7Tt/dZ/N11X5wXcq4aG201JdQOdbPeMg8H7MkpYZxJUqJkZevkpTtbn+GCMx1CQBxGsgDZdvgS6fuRfneNaxvazZamWZNFwZSM7yeG6zv2/jWH65es1iecnD9lGEe+/unPePzsY7RzKBVRCobi8XHAoNkenXP1q1/T6CeEm5foT76HH3dY61BdU80eQjCPPcas/6Tf8h99LZyye/CiVJrgZ4SoP08pInKk7TZM/ch82AMZ7RTNZkWz3SKlRQhD8D1KS4K/qeG+0hDDgDIN0Xt8nFGNY5re0HYt0hQa16JNx3A70u+uKDJiuzVCWiiJOEwoAzElhHZM48j65ILHP/xbPv/Zzzg6/4CkLUbkihdRGm0sIaU/6tf4nQuemnVUg8nuq9D7CPp7QrIQAkpCK1M/oIApeEzjaI1lLaEjcny84ebma05W52xMQu6vWTctcRiRecN8N3E7X6IWSKCQhRzGOh4pAolGKvDzBDmRY707RPEPWhGtCzkFSqnaHaks0zgglEZpR0m17VukgAQlU4ueJdRQCFG1JPf9moW1AzwkrJflc6NqZ+mb0LQM+Z5X9Pa+YO8dSwKWaI6pbh7U7yrMA816Tbs5xriGwzAxhwlJQuTEar1FZ03MESj0d9e0qw3boyf4MJFDwPeHGlK32lBK/RNTP6CTYBoO5EUkLlPBOFu7i6VQiiRnRY7jElSqmO5uaDYdMQfIgVwi9viU/vI5OgWylCjToJzgzRe/YX16Qdaa2/0dRd4XPG9vxVOAIhO6SGxU3Hz2JSpYnl8O9NGgjs84zAPNvqdZK/7ub/+a//0//Zw5SuzsMUohdY1HMVbXzldKJFFDe02zrvA5nwlpYn/7CmU02lmkaklFkXOpIlrtyMk/2GBlkaAUUxiQC53d6o4cEoFIQCNXxwx+wqaZAGhXCyQhBbPfE23CLSNViWHajSgcMUem3Q7XWZSyjOMepR3r7SlljviSkIMk5UJ5l2oeoGJC3GK8GLGmJfmIa9f0128o5bhiP0o9NBRRFnqvWyCRFdfh5552dcrt69fcvbxdBLKSdnVMCjO3L17SdB2bs1OEFIR+YLi95dFHP+DkvWcoJ4gy0upzrj77La+f/5rzTz/Fq4QXCa0Usp/ptluUaUi3hpIEcl4cR+vq+pzLgMqa6+dfPUBL36nL9f+z7vEvUlT2jtIabS15ccrlFMl+YNrdIaWjXR8h5KKqsII5zLXQEFT8gPRI4yBLMoYUFFJaKBptDMpKvJdEnxHSVVaPlKg2Ypxm9gO7u1ukaNHKUuYZIR0CTcqKKCS7/UDpZ0Zr2R9ucUpzrDUieFBzrQ9+x/76h7+i39mlJURGGVHFVMs+X+5bpZRlk0/LeCCCgugDOReiHHn0+BlHZWK4fo3bOG6vR0RwNdF3yLiD55HQfH03EdeSx0ctzmkyVSSbSrWH1954LSZU0dV6J0Wl5642BD+RCxjX4scRtYj6cok1S0ZVnY4UqjoUlCGnyBK6s+iUqHNxZcgpLwWeXOz4keCnh3TYUiIyiyqIXjZsKSHntMCz7oumt++xzaJSM1kq9WazZdpdMk8FRMI2BWE8RnXMh4gULchCThNCVRaEUAKRBf3l60Vg7gjRU4TAtmus6cgxMO529dIqjdAS1xh0t6mdNKpgHqmqrFhUMR4khG5RShNGjx960kmLR0HMiLnam4MPeD9QLLTuiJuvX1OsoHt0we3Nm+p6LW+9thxBwaREFI7sNK4557e/va6HkBIQYcLngf1+QnUtj5+2COHZ3+3ozrf1cFDALF1QbRzCCGjWS0NXwDyDAmMM7XpNf3dL0x4jjSVEv5xOJdFHSoKsFPs5kfyM22xJWWNbgxGGOA0I1zDGxM3ukuzWhKlnc7xmszpi6O8wVgGxFqTKkUNAzR4hqaOtdoM+cdxdfk0qa44eP6FZEAph7gnek0VECUjl3eC51LFczZkSpWDkkkOYIOVQtYoKjHMoJFFIkqgcrWkecU2LoKCVYOp3BC+xbYvUdVR4dPEYrS1lAX5KVbv30+01bz7/mv1hjz1Z896Pf4SVClEy43TAp0BOe86fPWW42fHlz3+G6dZsjo9xG0drjzCrLTHf0G4k8mqmiI4cZ8qJI00CvTKIAMGPnH70CdcvniOjqJqut/Ad+m9a9x9reQcJRA3R1ZI4DnV/DR7XdGAdxTUYU4G8ru3w44GSAsnXayx0qdC/kpFUA03J1RllXLNENmVKKqQ5o0wlMMfkq9Y1QUl1qmG1Qm/XxLngVgbl1+Atd+kWqxLRt7y5SazlhJUzcUxMwnF1YjhzA6t0UqNeykCmGkT+8B6t30fBI5dRkqgOmvoFim8q8FLluUKKGhlRIMVqSVtZzZG1qKknyIBQDcP1jnCU8Z3n8tVnbJoz/t3/8O/5n/+X/8gkO+YYaIxAakhCIHWDlJV1k2KisoEUOYVquRQSqUz1/itZg0ONRSuDn+eqPs+1+5NLRuoqBitlESAXuXRoWEYyCUQtcEgLRXrhHsTwrZOrFPUmQ1RTVk6LvqkGjgrJw3f1tq2lfkNQHQLzsANZZ7FCyspuiFTWSZrJUw+ikPOMNIppqmJwQuTo9DGpJHyo7dmUI9JVt4h2LRSwtkEKScajGk0ee7SxxBBQ2pCFIMWMlJFcErLy6ZBGY3XH7uo1Zb9HHK1QxmEwZD8T5prfZqwl9TMUwclHH+Fz5TXxrVHW284elEWRpcDHO375n/+JIC744Y8+5nC54733HkNyzD5ThODk8Zrz9075+vk18bhF6Or4qBk8ZSGLJ5SWZArj7oZmc4xpLCXNaK1o2w3D1Q3t2QlS1/dEjpHo58URpEgoQsmIWOrzOE4gazRLKJmYE3ZzBG5N8j3dao2UIJwlziNxjmDXDPsR4wxaKVzXMeXqRhJF0p1eMPW33Lx+weroCCklMXpi9ggt0EoRY1l0Wm+3kQCgkBGlFjxaKUoIFehZqCyyFDDWMu5vwRhEY8gShJEUCSF4KJlmvapUdGDqb9menxH9RAmB+XAgyYIwBj8OtM2KR5/+mGPgkG+YysB8GJFZUIqiv7pmfXJCmAa67Qk/+vtPefP6c4Y3rxj/ZUSfasw/SmQjMM2GiR7brPHDjgyksaCbluvnz3n0/qcIo2uopTB8q9n+ji+BXHSh5IwUMPaHBeKZkNLUbLkYsO5eexpq+HWxpHmiaTaQInGaqotLi5oPqTVQYZPSyGWsAVIpQoiEccbYBopCSYmSAmUapn5fyeglkUXGGkFjt9zs9rz+4iVGKD79xwtOjp5y/R93PG8Sr43gMAhk8WhVn7klhZJa7vxhR1zfuaD6dtR7jlWr88DgyZXaKaWqHZFcKjdlHMkhcqwtK3JtuzUN8zijkuXm1WvkquP4gwuOn63YXMBHf/mUHEbCLEiRRTfjkTJCqVC/hxaMkDWcUqpKIPE1e0tKg0BCqQ+2WGy2QsoqsM3VYnlPsKwGtMWKK3jgCwkhHsZ4YglIlVItwu16EUteAk5zWr6XhVsj74uCt/cpFZXqhiCzPj5ZiruC0ZrGbEi9oX8def3ZVwx315TYE4cbRErILLDS0ZiObnO8pMyLhygOCgTvCdEzh5FIYvQjU5qJuYpPhagW95Lyci1DTT/3E0JqUi54H+iHA75UXY4OmSZJkIJJZsZ5Allb81pbpv6Abddo15CWJOh7OdrbXuyAIBSJFJmPP3mf/+4//AfWJ0d88dXnNGdbzj96yvGTC4QupDKBCjz99GOUmLBOImQh5jr6iznXziqFcerZ764IKdBtjmjbFXGaiZOn67ZsTy9qLIRpKbmQYnVlSK2QAtLcI4iE8Y4cZ8I01ue0dRStan5erliHTGEaR+b+gMwZWUAoQ4gBITNzmDjMIx4Y55HJDwzTgRBntmePoWRe/vJnFF8zvaSuyAPj2rf6Wfz/WmVx9aiHw1d9tvw01vH8YmlWWkOOSJHIJRLJTMHTTzMIjTUNRjvSNDPd3RGGEWUt3dk5yjXYboVuW4Q1HA6XCOVRShDngJItpj1inmZWx6cY2yKUZp56Xn3xM4xVPP6LH/LBv/97njz5iN3/+XPEYAjrFaEtKKPY2hVHZkur1oSQ2e93bNYXyD7hkq1MqbfeQflvXYXoZ3KuhPqUU31nLp3TlGN9B4aZWDLT3ONTIFFjPbR1lJzx01iL/nl6COcOfgKo42nXUrO5JDkJpLQYu6oHSiWQOhHjhJ8mlOoQwiHKhiEUZnFNwvB67oh+z//0P/4Nf/OTYz46M7jrV/y7//4Rf/9DibSW3TCQhCQjFp1zQeU//JX87tESCyclLy6ke/hgzWIRS75HemidpZQWgbHGlAJ+5O76BWq14rC7I0fBl7/6ipOP/46zH/419mQNZeTD7/8FEk0umuBT1QSQESS0MYtiPS0k40gMAakNhcoJiDFSUq45S6Ja/MTysChT3VX3QuN75HwdW+VFi7QULEshV4sWWV8sS+hlilWTAveFoFhEzJl7aq+U1Snx7ULx7VuCyiePCBJSSLSytG3LeHtFmhNkS7s+pdtuWD06wp52yM4h2hbajiglkx9BSmKY0aY6CkQplWck78nKhSwKRUlCDMtLO5NSRmlbi+iUyCk8AB9zBoEhZ8E0D7jNEfFwwJX6gpgIJFkftm59DEVw9fxLlKsuMz/0TLu7SnIub/uZv66iNKJEOg2bzrI5u+C279Ena/TphqkE9NExyRnEqsWtWnKciH6glITUhhgTmULKiWk8VNGylDWRXEE97dSxVc5QcrXDTn1PiglxfygQ9bDSrlqaRmOsoMSppqkrTUi+WqKNIviBcX+L94GUJdY2EGPtx2SIwWOtAi0ZY+AwDQjrqk5O14PMNOyxruW9j35AtznizVe/4fXnv6oHleXZfZfWg65QgDLuwUhRSj10CqWQWi/vPZaOsyTnRAKa7SnzODHt98RxIodE020wtiHmRMgRZS0x+OrwMRoIxMMNao64ZFibLaX3GG1x6zUhBuZpIpVIe7zBZUm4fsN4NrD+4Uccd9+j/+0t1y+/Yn1+gVWKFsPGrJER7l6/ZHX+HvubK+bDAS3vpQJv83v0376ErGMnSkE7V3Wr1iG1JoS5HhSMqYUNmWnsq+bHLILm+6JegLYNylpySmjriMFXt2ypDuZSCrZdAxKpLK7d0K6PQeQati0kYYoLsHfEjx7VrCmNZPKFN1c7/pt//Anb/JypTOzbljEnzOkt3z8NnE8RaRrC8rwDtSv5R3jTfse7RaB0JQ6XlChpGQPlOgL65uQk65gpF3K4t0dCP/VEAZuLJ6yOT+uDtFrx+vUtN7uAu/gAc3pBDJGr337Oi1/9CzHFKqDKAi0dJRZKKpW1EmKdNS7FVfALHKlQ/12s2pOSEkIZMgWhJCknhDbLS6Ha/tTy6/uOzQNrSC4FzFL0sMQiyAfXVv3EFb64dJ6oM9SHoDZK7Rq9pUugFmtkoSRPCjNGN+wuX6Gtwq4k6B7Vgt2uefZXf8XTv/gRh+GafjgQUmYKIyhFTJGUa3dNKYVZQiTzPNe5taho83kelmsr8ONUTyFFgNBIqTDKoIVCJGoMQlYYTG0DO0M/7Blvb0jzTMiJrGtxNO73kKvlNXjP7vqS8XBXu0JquSfegQaAIqOEpF2dEHxhmgJHTz4kl8Lh9oZm/QjXPcK6U6TdEJOiYFC6RUqD1gbXNFjboKWmbdcYbdFSo5WuDiwjiSUTYsJHTyyBw+66MpRSPRRBqYJmo2icZbVpMYZF0A4lxhriqxXteoMzDmtMPSRohxQKXcCZhlwEpQhUSTUQ1DXoZWM22qKEomnXWNcC9T5y6y2nTz/k7MmHRD9zd/mifkHvWJfn3oKeFjeoEFQ+klI03YYUI1O/qyN6FilCLrSuRZEpKeB9hX2uTx+BVGjb1GiCnEghkH3ANR3pPhMvRtIwIubMdHODpNCu11XKkDKu3VQ5gZXYE02zbunIEsiMAAAgAElEQVR/dc3Bj4i/OOHL3/yMzeGY8/YR6bbn8OoljWuJw57N9gi3WnFz+4KgEklVYYt8dxU831riQTYBFcmSKQsnDJRzCFX3VCkkogisbbDGLSDYyoGLfkZKtTiEZY0cWYJi6x9T/1m7nwmxTF9yDtyPe0sBKQzatBjbYpwmhR1aFAoth35C3r3hg6drpvI5/TqwbyTp0Ql69T3Gn88czWtSKMSQkcpWza/goSnwh1zf2aWltEEZWwuABMlX9bVcnBzVtbVs9inAAkNSzYpZzaiTU2TqibZFOoPrjrn44Y959eILfiDfR1pByQElNDlHcqkskBTmijmXLXHyJEotquIyIpGKGOPycw2qVFZHGJC2RtnHEJbGTUVvK6UeROOlHlERwtQ56Le8SVKqamFfqmGBwM/TQ6dHyiVxWC0sIuTyey4C6WWM9tauheSqjcE2DSJlDtc3GNdhO4XbKFx2nH/wCV/9/Jd8/fP/i5I85+dPGW5nTNGIoqq+SmtkinWEWECKUu3T2pFL7fAYU39OiosIs3bytK3kbBFBpEiJhclPtTNHQFuFXhvkpsWdnbG/uUSkhlFkdKotdiEkU3+g25wQgielwMX7n5CmzDS+qdqT33ESvI2roJKnYHn11auaq/TyFaKJdFKw+/XXxMOBXE6R7hbz7Amvf/sVQm+IUdDf3qFFxLXdg4hfaY1QhrK8YGMOyEItJqUmicrbsN26PmNUbZexNehVS0nJHqMdbWsfMrByCJjOEqceUaDr1mQ0m6Nzbi5f4o6PWBsD2iDIKARWVGdmyYJxt6NxhjAcaNcnlFyQ1jAOe5r1hqHf0f6/5L3bj2RXlt732/dzTkRkZlUWq3jvnp7utqRuyYJmbA8M+MGvBmzAf6Je/OZXC3qyIAmwx5iLR1aPpy/sZpNNFllVmZWZEXEu++qHdSLJNjSjsdlkI6lNJKqYmZVFxomzz9prfd/v25yRSmL39C3C9pYXn372+75Av7vVWEGngtQ43TdU2ZdareS4YK3DdIOIljHUdMT3QY4yrVCspT97zDIe0EZMATlnAQkuM5SCUZLQra0R+nnXsewP5DJxcf6I5htFJVRTKGPuuTGoxtVewigvN48YP/6I63zg4gf/ENsCd3/9ASW+oj05Z55H4vGGyx//A17dXXP+3rsoo0gvX9Ku9+hmqd+yYvU/tJQ22FWLdW+WMUb2wXXCQY2UGAm7c5oy4ixVhqYVJUskTDzuoTVylbgk4wymCZtHCiIto2cvoytnOlqtlFpWd1hHXqSxgG0YV/G6EFThMFoOxzueusQb/ULqN5Th+9Sfv0bnI8//6mf4Q+TZH/0BP//Jh6Rpodv1Xyp4vn6DyFcWLdda7rscdbWgayPiqlblIVZWG512W+qyUOYDfqcZj4rX+z1ndiEfK3le+M4fv820n3j29jNQd7RlD8nzB//oD/neT/+G4BvBW2ortGaoVdHQKHWC/GlyitK6s0L8LTFKUrkSyFguDW17VBNgXWn5/gVv6z9aG3GTiGBorXpZiyCFVmqNvVf3bIRWK0pVKBKcqtex1gokWf94QZWTlf1h3qgnNb9SClUrZVnw1uL7gaoju6fv8NFP/5zDzZ/RoqXeFoI3vP2DH/LR1Qcsrxf8pqJMkzw134voO0cKoGqS9qZSeOdQWokAUjWct1g7SCL9QVqxOc/UGum2j2i6gpZNcJlGxqtrulYYegO1J7gNF5sNr69egm68vt1zuL7h8eNL2Dp021FKJStpEeskNOAHXfE0QBkMiqos11efEPQMzfHWO5d89Jc/peQ9j999Srk94q3i41/+AuPPcQaC92jlaCVSSyPljOsGaafnhZxH3EG4WGk60O+2uCAZc0Up4vGIaRbXdSjtyKUxTiM1Trg7x7Dd4LQhbD0pF3JpawdhxoZKU4E+dCz7RFMVZQPKOlxJNOspJRKXUU61PjD0PTd316hW0EazjHviMmGcIzpPWhaqAT0dMLViFcRWHujd+NvrlKeplMIaz3S8ARrWDTStyDlhhoGkF5py5HykDxucF/eV6zfkFAmbHdO4Jy4HNp3w00rNWOVRWgwq2jjhwaRMbI2UEzhDf3nJcT6gkxS9ZVnwviPnEUxGe0c9NqqrmHcs3cst/GTP7r3HnF2cYeLCZy+f81b/BqOd2F5u0PtbHg1n3OYjNmpyLv9J9HZOq7W6yiZEdN6UErextffwW62aGAlqJk4jzkmgt1nP1mUZoYmxp9YkoczakrN0zJV1oDwxTeQ6QRZhcSp5jaQxlJpQFsiFJS60bMUZ28lZaEie87OK7o6wecphaZS7jP1sJmwcZz98n3x35HyruHqZWfyERUEzNL2gmuXrfC5+9bR01FpgiD1Y6S/dcNbRSibVJi24Uqgly6inTLRWOY4TQS/Mtze89d3v8PjZGYdPf8JZ9ycs15/R7g6kg8U8Klw82RLCFrWC6EqpoKt0Z5zlRHl23mGck2InRbQPlBzvK+NcG7XIaEajVgrtSWcj7ipWoZ9Y99a2L5VaGwrpHLVaKaXcf0/oNzICyUnErlTU2uWBL2brp9HZg11rGW6MJceFVhL9sCGVTEXx8uNPePLOjyBWxutbWgykfMVHv/w3PP3hP+E3P/01uVp0TCgjRWnOmbaOC43VYq2loVtBlSLOBBDnidI051HeYKzDq0BpUbo91pKr6BXC2Rk29sTXn9FvB97//o84fn6NUgNhm0m+45PpFu22QgfWYBfN4eaGVBq1yVhAs9Y8D3UpRcViUGjv2Tx5wln+lP7iO5y9Edj279JvHE++e0Y1is8+Sby++be8/b138UGjnSLnSuc91nhYEnGZsFoSs2ttpHFGlcrQb0g50aoXzU+tWO/RtVJTBtuIBVKV1nhOivF2YrPtCUHyfVKseKMlCboJ4qFVcFry0zJQ5hm0hVqJtWK8wAetgZoFbmmNFtGzBt8PGKVRVUbT2mmW6UC8G1dLoeXrzvH5JpZSa47WOma3zq+ajcB4uMV1PXdXn0NMWKMwTtFypB821JSYl0kifpTBWgsEUEUeeCswVfg9MI9HOmsxdnWDVdn7luUArVJTQxWkI+iEe5ZzpeaKsx22D6RlRvcb+seXUCI+H9h8x/P4v/0fePEvfiYF2qMd6RBpTfPq819yZs9Q3qEw/8mkaYnofCR0A61VIWOvz5GSE6HboI3oIdGKsNmR51m6P2UWyUkr+O6Lw6WxjpKSmD6WBaUcKIeyPbkuGAw1I3EWWjSUpWa0AmUaCkcuhjgllBqZlow6LrzzT97GvXnJbbvCPkr4N3fszzz+O+dMw4g+FPrQoBmWZRQ3LhJI+zsKf/hb11e/w9XJmr1azP5fYtx7e3ot62ioYZ3FeY8eMjc3ew57z93dC86ebXj+N7+kxkbLmeuPP+fw6o6XH/2a57/4Ba05lnGklLKO0oxY4lqktYVWMzktpJjJqZFjoVW9KswDYGlV4Vwv1ngtrh2hMbHa/vgtobI8gKVl2EpZxcvcFy6nNrE2AhM8odrFqbXejieq2Zdaryf79kNe03jHYX8jomAKpTTyUhhv9oyvb3n1yW843N0x5xm11fzhf/1PcRcH3vzhW8QFMAFl6kr+NBhloWpKUaSiaMpSSlnRAQmjLcuUmMcZbQw2WJQRMnZdiZ33WioUNWVUaQzDOWfnT7m9+lxGn3PDXycGp3n8uEPbSE4afdCUm1vq4cim2+Lc6s77mq2SX/+SriXGMo0jYXdBGAZKHDneRpq6putnaqokPP/uzz6k6S2wUKngPFUbcmvkmjHBY4MnzxO6NYL1OB+oDUzoqWvHNy3Lvb5OWU+plXmaKLngvWe73crhxAYwgVggVkhV3CV+2DCc7/BBY3XD6o44RVKqHOeZwzwxLhNaaUIY8D6Q40KKM91mxzwfyTnJaLtWlvEgQcDOMR/uZJPXesVqPPCbcV33GAVgmde07FqZp1uUbaAL/abHe0PfeeoyQ6mUKIaAUgvNmpVaX7HGyfhZG7TRtKpoCRQWo42MHsnoVtGlsQkbyvFImWdaqxQqTTeWeWQ+HFHVYdpAHy7Z6C3uLjHub6jv7MiXleE9T/8dS/d2z/kf/SNu8kiZGuPVnu78AtcPhH7zRcP1W3Ld/mOrlizW8HUyUNbMQdZpRK11xXQEMewoLc/GIuadUjKtQZxnkQqUIk7YZSYuibQUSqrM+zuRLCiH0gO5GJQZMK6X2CY6tOowWuCf/WBx1mLsOTFVxnxDeLajbi8o3SU6e9qi8M92Eow+NMLjDSRFS1WKZdWoChlNfs2X83dgS+dLIuXV3VSrBNXVun6t3p/YjdFS7GhFt91yuINXnzeaOwfd8bM//SnGyikkHhU1d+C2LDUwTRltPCXlVSMjsfLagO+71XHgqaWSYyZOCyVLhldeMjTh6tQixUupmWY0bSVYlrU1qJS4O4w70YOLjO5gzXSS3xvnVvu7ptWy4tmLkEvvxcrlSxyfNRdKKXnzPuCWbGvCbAnbLfMy0qzB+CAxHAXGm1u08ZjQY+wR2xrLleGXf/o3vP7wNwSjCZ04OFwXQIltueZIyZWcKko7GpqUomADgNrkeuUiNsxcZnJe7juHJ0Q+6zMsTyNGa7aXl2TXGG3m9fULDh895/KNN3nvvffZne1oGMo+sQkDz956n+32TK6dGDt/3y/3V1yySca4sD/syaXiQqCkkVpnQvcYbQvTcuDf/x8f8hf/21+wu7zg7GJHrYm7m2uU89IpbYW4oun7occajW4VZSzadyjnBeg4jSs2QAkfyxiyaqKTSllQDdQ1C8+SS2EcZ6FvK9GLlALH21vR6jlL123IaxxMKoXDdGBJEVKGnMlLlI6G89KvVYBWWO9xvqOmRE0J6soPMwbfSYjwg+64fnmd6PbO4oYB328kM4yKD5aaJyAjEsKyFi2LPOiUxvggOktjoRbm/Z6aBS8ibsogRU8R4bI20o1tNeOsGAdMhc4PbLYXK3E7yMHYBubDyP7lK6abW+phZnl1Q3dxyU265aj21I1mUdDmyNI5fvjf/4/0u8DZ+Yb+0SXa+zUL0a6HyAc9bP57r26N2jnpQ2spdMP2two+bTxKWYxx5LRIRmQTfWRDiUMaMfHknFdjQQPT0QjEKZHmmZYzNEXTnqoC85xYjhNaW5Zx4u7qmpoqqlRaHnFBM+1HarFgNefvPSM7Qze8g/3wjJ/883/Ny7/+mOHuLTbLm/T1CYqAVm4175z216//efiV+0cndo1uJ3FUvo9TqDI3Wum3opCRwMCCVgqtA6lmbq5eY0Lgkw9f8Or5LT/6L/9z9revwFzgrCWWmU8++4SCJceV8qkVNScaZU2ONbjgxf6qDMa4+9cvRwn9VOsnSpYRSU5RXuq2jttSJNPuLfX3nmT9RasYJRtorWLPKzmtIy/52UpL3kmrp1iJ9YW6t7WztiEXTiLoh7fkdeh3F6ALKWda1ZALfb9hOBtoqqF9z+3rK3qrKPuZ53/1Mb1+m5KOlHpLymf3I1FjLFoXoXGjsK6j5EzNSRxc2pJywhhFK5VSpGtRciQMA7XMgKTX1yraMqMMWmW2jy+5PX7O63yDffIWKmnufnLDmwXU7ULAUAaNHRdiXLBGU5QCJBtOKfPAd9V1pIxiiQt3t685f/KUsnxKCAXjHpFd5Ppm4n//l39Kfzbw9NmOoBt92LLfH4nTgrYFrarYx1Wllrq2zMWu7vutdAlKoeSKcx0KTW2NZRHrbMVIEVQa0xxpGUI3kJYFrTNdvyHWTIsNVMc0jRSdsU4RpwNPnr1NyQuqFbzzGOfx2mG0ISYRber1AYsStEEIHcF1eC1smTHOouPRGeMc1gkg86EvKWvvRTxM0wFvLN44OhvYH+4k/67roZMRle03xONxtSGDUha/6nmGfstyPJKXiHJGunrjiKpIQKi1YvhYBE8Qa8Lbnm7Y0lpj2d+BgYIgJKyXEWR1htB5lKn4Ny756MMPePXymre+85TlZsF6z8EkPv7Vp+y2Z6SXv+HRj/4ZUxw53F5jSoc+fwQ88Nvy/8taXcK1Fhnday1ygvVgbawlx0yuCRfcGoXTUBoZP4eetkpPShG9basVlGOZCzk28jyz220Qrl0hV3G75hS5fOOSlGaMC7TQU5YF24njLo57QndG3WusHuj6AGXCmIE//5/+F/gkkPWeD/7FX9KeTbTbkd+8qLTN+1ivUMuEqqzdk6/3ZfzKBc/Jei6iKrEWU+r952vO92OhpuRBpFCUtODNjtZFJq44zls2m7fon5xjttCsptTAOI4c55n9nCjaCdPHri6rkmg5SYaOqVgvzgTByy/3lGVtWWMdhLuhVsdCWS8stVIXcZe12CQc8T4VXdrEarXbt7Xbo9fChtZWCztyakStQu4VVKgkDPMeigj3HaKHugRspohxQmk5pc/LiFeetOxRypHSjLeaQqJVw9nlO6QSqe6Op9//ET/7s/+b43HBOr1aIBs+OEKnWcaEtQO1NVIpmLCl+R7VMlo16jqyUtqtbhTuoY9aG6iSqo7KwEw4HzjWW8z5OcMP/gD/TqC+OLJfEu3VNedP3+Tu5kMUB3R/xrjs5Uop6dDJcfibS/T9OpZwVhoYzzSNPLZPyMuRR5ff5fbuNzz/+Ws++vWI2+54/MTy+GJDoFHTTOi20vaOI33n8aGX97YzLNNIKYmWBuosXZ1+c06cZzmIVAAR+Oe6auCaQ63Mo0aVzCQaIXicElREavDZrz7EDVv28x1dZ7nY7Wh1oe87llm6Mt536NJopWLX02JcRMyJNtS8MI8Hip7ZDucoxN3i+4H9i+dsnj0mLcuDPHb8h1arDbToEZ3vULVScyKEXkTEvYDlxuMtRmu0c5iuxxgPtVJSFtMFDaMNu/M3uL29JvgtSitcZyEVoGCMw4etBE6SaFYMB7YpKTytFRJyE81HThNu8KAsqszEMqPfeIO7X9zyRv8uu7pjujpw/nggPr/FLp67q2u2e81hyizLkbDZ0peBpM2KjFDfmmv3d63WqlD8taYWqQoEzyJcHpFRVHw3UNKEsdBvd9AK/e6CuCRQBtcPMuBWGqXhcHeglkBOFet6fLfBbzVLmpmXhgmiv5vH17g+UGKWvLUCaTyK2LiMEhVUBvbPr8mHA3QL+VHh7X/6n/Hphz/lu//Vf0Hxld0/fI9yE/lUHzimjsottjV0XWUiX/Pr+JVFyzR936TQaEnRPulfAGWEjVJSRhuL0QplGj4EyvUVxEz3aMCfBWLa4wdHdhaMZf/qBZ11HOeE8xrbwCmNcicktqGZTrI/MpRyRGtxa9UibBenHaBZ5hGa5MisxS96JfamZaalshY50gHSJst8H7HVG+vuRcjmpBNRYFaaM63ICGb9vPwiSdGlFlQTJ5nYCdXKCjp9PCzHljQ/pPq3VgTiRWtIUEpBqS3Hm1cc9wtVadRmQDvD/u4Feqgsx4VgN6ScMUZO4WklfvZdJ69pmrChw1qL8V7eZkpE8CeHiOs2xGlcu4iyuValaFqD9cRxZOg22PMN5e6ObvMY43pefPIL3PkFr65e8qTAdjPAZyOpKYrxVCNjSO08epaN4huAgH6NS9x0xmhs6DmO19zuR673I7/49UuKPvL841ektOXyzR1njzzBGuo8U5u4Ir2zUBQqJ1QBawNLjjTjUNYzH47UKqDRUoSvUVeEgNIabTusKsRlASppOkoAorWg1jFwMXjl6DrPPh3YPrtEuY7puKfb7WhGCNm1gR92xOlAWmaWlO/H2qVUalVU8RXQbR6R08J4d433QTqH2uB0L/b0KCDLpswDugP/9iWcsFVWUDIKRMxaK37YkFtmjiNNG5a7ibCDvIxUM+NcoNSEZOSJezXXyO7RJcfDDZ3d0UqjVunUoy25QtESMmm9k0yzrpffN2Tc1YSWjQ5Y05HGxHS84+ytxzjd8e73vk+cLU/f/wEvf/XnnDuPvpp4vHmbD19+zLPLd7n62Qe0xx2bbovCSIJWK6ivWeT6e19f3nfWWBS1amWV1piV2l9SXEOpC0q3tRh0KxaG1UzUyDlKppoWnZ33G5accVZjLdhgCF2HDoGY7qirGzfnRKd6CgWlIv1Zx/5qz/56wnUG+pGkBrqLR/RbiafI04F3//gJ8ydXHOdEmX/ND977E35RFDXMmLKgq6UpS9NFaoev+Sb86i4tbb/0b4ibRmspcNaLkpeEQoLrwtDL6cNqpmPEmQ3stgyPPaYpXnee4ywI89evPqffPEZrB+mO7XCOUQrlGsYGSi60qqilUWvC9wbjZKwmuBCxraeYACuiu6YpJVNpaDS6QkuS5F6quHGE8fTFyUFrKzqOdRyl9Jqx1JB09bWFfOIMKSMgr4a670agtcSFNjmFtVPVpVh/0EPrIGis9pgGKldaSoDGdTvubq4Jm0sU4lDzXnO4e8m4XzBxx6d3n+CVwXpLrBFQNOWY7g7o4gnBy+vdGqHraUajjaXGhVrAh63MsXNGKSglYa0jlwzKYEKHspZ4PJBNJdqZYjItRkIubC4uMJuFu88/Yfv+exQ14nAc58i+3MmlMJUUs4xkxKT3oJdWCmXE5YYxHMaIO3+Ln//qY7aPHtNfPGWnKoaMaT1pOsocv4Eqs+gBakYXhQ1b8jq2MrZjnidoirpElBUCr3bdmm235sdVwTMY52hF8s66zsu4mCY6u9SoUaFNo1IwgwNd2JgOpSpzjpimSeMojqGmRL+1aniqyZK4nZvkaPmOeJzxXcBsL0jzSIqR6Dp6b+n6Dcu8kHJG2YD01R90ZSvHJ70Sqde9qilY8sI03uG2HX7YYT20BVqZ8cERlxm/GWgkIfc2LdIBpyl5YbO9IE4zNjgwmjgtuG5LTgn02mlDkdNIsXIg1C5QS0abtppXHHefv6JOkFphvouYpdB7xcSem/klx1T47DDzaDiHduRyG+guNnTlwO3NzObZDn/mmPZ7lK7isn7g9+bfur70VkxxwTrLPB4JIeA7R46n2KYsBG1dUCpjnJX9cZ1kpDlS8ogJjRIr2nSgowSIrgea2CaGsx2YQk4zygQUmnka6fxqWa+WNB3IJlPqhN0M9O4xJRX0cMQ+Utx8ajiOmaFcc/WLa8z5a976k/f54H/+OWfnO27/+kNexh2H8Zqd6XB0LCrRdMbUFePyNa6vVPCcZsZtzaHSWt3bBFqtNMWq41Fo53A+rGOfxt2rz8EGnGmkeMuT/ruYWtF6ZtgF3PkO1TTz7UjwO6rbEboe66CWhDHSmm62UZJYKWlra7Zp+bq2a3aIJPvC2tpvCYzAA0tOVA1zmjE2iP7HyvfXksX6uM5J6yr6Mmr9XJO2b2si0pYWbqYVJQVeEwum9aeWoxRSZR3rPdRV1Rq1WAtaGZyxkpdEJeYR2zu0FlF3XibG5SjFoLVgNKkkyW1KlaIEdZ6nEV0trz99zsXTZ/RnF9SiKGn9cyIGQKMoyyJCcMGAUlISR3FZhfHaolJhU3a0T4+k84l8tzDnK9ThMc0Z7HLgPDb0oy230y2qs2yVJzfpSChnaUj2T/sW7Ki1NtE/tUroOmqJ7C4esaQjrSxcvPk+VhXyLPk63g8yAquixZOxrUZ5w7gcUCd6ekyYsjJS1/GJMKzSKiw97QFt1cSJLkpOow0bOukwlEwBUu2Zl4lmDOPtazbnF1jVyHEmA2F7Tp5nyhpv0ABnPb4LxOVAy5KvZp1F14YulRYj2+0FRikO+xsomfkotnplLNZ70n3H9YEvJafkWjK6QUORa4EIQ3dBXEaaL/dxBD44ORyuTCXlHDXO0gVQp0NYpZRIbUl60qpQWyJOB1RraKNww1YiIK2Vglcb5uOetaLFDx3L/obh0WPUmWE+HlhuX+O2G5TtKNPMPn9K1oUXHFnCwPYqUvcj+8uFu7qgS4fKFe8NixUHmNIG+HYwlP6uZX0gx4nQixuxpChC/CJGDaW0IDtqJdd4n6GmjcF6QyVinUa30yTGoLyjVcktq1XTbweMa9ScpIOkVpbcGoKdS0a5QGuKaQ0UHR49ZryOpKni+gncJT/7s1v+m//uCU8OHXPfoY57zGbP7q0/5tO/+ffc+ow1mtB1UOXaNfX1d3fgK9bGp+1BGyti5PVDbNrrjLVWtPeig1CK0G1oueB9j+0GVFAYB1Y79i+vsV5x/uQSZzXOgnOK6e41IexWx1OhGzbSo2siytK24YJjmY7Mh1GyfEolzqNceHMK7NT3VvPWhP7ctML0PboLYDQuBOFMIJuGBIXqletzKlo0pwDRL6rr9WopydZS69hLqdVC+KVgVZlVPtzN9d6BViqUilESNlFXV5MNjkoEnQRg5Sx5HUO40GF6j+k9Knhct0U1I0AzhN6LdtIuT5laGsvhCEU6cfF4YL59japQl0hLGbVGVBhrMUpjKqgl0XLE7TzhvOf86WMuHp9DOhDn17z46V+QXn5O7QPZKjIFqxQpSjFVZqHJnpwgD32Jg1Let6ELlDhideOt979LWw6U5YBzDrfmysm9K0GFp8NCa40lzmCNaD+slawkK/EPoe+xzsmYMi0oVkPDvZNHgJXWWqyV8N20FjvGaoazMyH2+o7peMBqiwGcM6g1vmY83JJKImURusvfZ9DGEfpzcpRwzEYhqUTShSlNjGliPx3AOkxrwghDUxqSJv7g0QOsDhzZVzRqZbaIzkUbg9WWYAdaqmJXDhplZW/z/SDejRQlswkBzc3jgVwSyih835HyLONlrVnGA8fbK5b9LYerF+RlAaUwxt6Hl/phi3U9NSuG3RNc11PUwnC+Zbs9x/YDeVqYrl6Qxlt8cBjfs19mxus7cm28VHv8H75HN5xzePGKtiTKEkHpB++f/PuuNE9rViOkZURrkWKkOKOUkmfO6pI+udhKjmsHTmOD5MvRgFJxWlx4OU3kOFHLQqsJFwK0RponKWZRIl9AZCkpJZQJaNezv7nieLgibB35aMiHkWb3/C5p9CUAACAASURBVOW/+oBXH4Odb9GfPmf+yWdszgqb7wReH2deX814a9AUKXpO/LtvYKP96uGhSGhmLYVSssyNVxX5fdFDuw/qmw63ON/RDVuG3RkpHahlJkfF1fNrdLdhHkfm/R3WaIbtBqMaZRnphi1pnmjNQDXM45FlOlLLQjcMdJszrOtJMd2zce7TglcHT1pmETOjpNu0vklc3+O3ksOjVkW81nJaEUKyjOrMGnbWWru3qqMEwifha9IF0mteGHDfLZKYCSVAxJwebMlzes1s12FCED1AnGkNprs9NCls8zKhVJOQz6YwylCWGWsd2mrs+iAzqmE0hO2AP9tiNz2lySartJzW0ySIe2UtYXdObZWm5WHVasFqC6VCLhgU4801Szsy9wfKMOEuFOg9ut1w7hWXl0/pnr3JdJiYxoVlnGhGY7sO67zoGWKUGfi3gfWxht5KtlLDOcN89xJvYLMdaGkmjrfE+UDJUe6rWr+4H1YQp7Hu/vqnZUHwPk4IsNbSbzZ0w4ZWhJZttcZpg2lNcrGMxSpNzYmcZubxjlIixjspjHSjIYC0frPDaEeKgqMYug3OetIiehNVKipnqJm6RPI4411PKxnXOVrQVKfIFvbjLYdpT6atugfDeDzSlFDbZZz1LVhaitWyLORlBc7RpOtqtURMVI0zHaqt2UulYtA44+Qw6gJaO5Z5wa2gu0alNrE3pyWvt1qlNEVGkVbbeo7idnOhk8JHgQ8dVhnKFMUCPx2oVWj4MUdqKTx74z0cBecMGzrUyz15LriLS9zFGZt3LvFnhvMnb/HyV8/RZYOqGqUefqH691naWKGXK42xfpVXVHzo7y36JacVHeDW55NMXUqKqAaliOA4lySsJeOEsKwtvtsyHfaMtzfQGsvxQM0ZY8Q6bq1HURh2O4btjhB6Nudn+KCp6oYuWC7CU977wWPU2SX/5l/+gubO2GTP+PPCs+//kIN9yWgLOEcInq7rqGnmS1Clr/91/Ko/4JQ5BbLxndpoZgXxncRVrhuIy8QyHqT1nRJKKba7LX0/cLjaMx2huQ03L16RxkQaR1pZOH/ymFYmjrcvAc3Ni5dMhwmje4xx9LstDfl5tTa0sl/i9IgtL8VZODsrAdoojbcB5zxGGxEwK3XfiWq0tRsjEMG6BoEKh2ft/BgDqN8KX5PiCmqraGuxLqCNxTp/DyU8vS4PdelV39RaQwdPUgWz3eD8Fqt74n5k2R9QVeG0I80zodvRcqULGwyNVhKURO8dumacN9jOUX0jtRntNMZrXHCrkytTapS2edeB1eRaqApxixiP05aul6I4DBsuHr8HY+D2g5f0047NYYf5KKF/doW3Hebdd7n+5UeM13uMChTraFrhQidFmT4laT/U0vSL1VbVdWuCS+i6js1uRzxe8+jyCdPtS/phQ+gHEYqfDgprFl3NErFijcUZKwRza2gaUpHiBarEO4SwiiUFSGdaw2mN04o+dBgaeu1EuNDhQiB0PTnNlDyhSOLYMo60RJZY8N0ZTlm8DXjf0Q87TIU8Hqk5EpeJkopgK7TCWE2LC30/MPQ7dDOQKt54dCukaQJlpUtQpPP0bbjOlXbffaZUrPOSbM5MUYscvpaCUx3EBrFIwGQukMt9VIx1gWWeKKWirKXRWOYDJWXiGIlLoTTLUmCMSXguqyO15ESOkfm4Jy8jZdmjSsFiITWs9dLt1lCMpqZMbwIb36G8whR4o+4Im3P87gx3c8TPB/Qwcf7sbW4/3RNvFaZZNPXb0ID9j66c5fCV07Ly4oSmLRDBTE4RpTRh2N0/W8yaFWiNo2bR++RWyBoiUnj4sEPh0KajVs10nIjTvGpx5Tlec1rlG4qy7KlxpsaJuhzRTNRyQLtrNhp2Xc/ZH2z51SvF//qvfsZ1eUT0b/Bqzvz8l7csqePs0rM932FUExPKNzjv+IpP3UotEWXAeCPUW1XW00AVtDwKYz3GGPKyYExgf3sFTlPriDEdpI7rT56jNLgg6cZGacqS0Qhzpz+Tk1srYK1E2zvb4e0gOhvaGnkvya41FZbjKBfchRW1cwqo1PcwLkVbH+ANrRq0tI5ohPx7Sjk/BaGewDpS6K0uNC3tRLWqmtqXLD2tNVop0mYv5b4tqU7D9qZ5aEj70//fMh2Zxj21FKHWlkawHf1wJsUCgHE0Ld0yp3rqPLPsX5PSjDUeay1h06ODAaewwyDIgHmipYxVCkujD4HtsCV4BznitGXjN2xNz9YO9E4SsluTRo/vz1j0THukubr6jLtxYhkau7c3OHPk7A/eZhoctWiWw8z24pKYj5SYuDve4c4vJIumZiD/Pl/u381S4q5ppUk3NkWssyzHA91wRmuKlDK+3+D7nmYMKUVaabQMznSU1ChZQnhVrVij5F7XUHSgnk7craCUpRXQGHGIrePfmhPBd3TesekDZ+cXYnOnMS8jqSSx0vZbORQ16RAqpGiygEWRjgdqKfh+Q9js2D5+ghk6TOdJcSYeJ/JS0FWja2HoeoZ+g3eBWprY05UhTTNUhebrF0x+E0s3eRAqY9AhoK2IxGNchJOG6G9aydIVbUpEp8qgG3RhIx1wBf12KwSnE3JEW5wLmBOBvK7IkRXj0SpYP6CNGEp8v0FpSGWk2QIeqpIonpwzxnbQDDpsKAqGzYYn54/Jt3eYOKL7guKO5TcvCYdCONPkOvPdH/8Rzz/4GQoD35IDyd+9ZNgjWY1qNchIlthqiJbOq7GiLV0zHJWxq4mmMo9HlO7JJWKDPLfikjB9R9OVpiulJtG1KkNRGlTFmMKw7bDBoC1QIjnOGOPphjP5/ppRZqHVA7YsXJwXnr7/Drfpgn/9Fz/h/3r9Sz74/DXjIeCGRzw+P0PXRtWiB1UNdIMH0OFZITXICamRaUoQZ7kUKhqlA9oYcpyxNkBTmNCh+w40pGNm/+LIeHPFo2ePGM42aFVx1mKtoORLyhin5QTaDfjO0206pv0VqjSMFvpnKYlapbMThi2+3yDaVrf+56q18EnASkBuFW3UeiqtaNNQbR2NaOnMiAZBZpkn2NM9XVobGmr9O0SsrLUVUeYpYqI1aslysqGtjJ6VaIhZPx7OZnvq7qDEhuysx1QZXwiITjg4TWmwBlolzYuAq7xGe/B+Q4mVZZmZ5gNFyUjU2w4pcQwoS0PTGmitZMTZD+hacADTDIeR+dUNdy9fczyOjGlG7Xpqp4htAu/p+rf59V/9lNclsxhFLAt7NXE7XnPIMyH0xMMd24sztmeebCaO8Y6cVnfhA7o2f/uSh4LSFpSVFG2t6DfnHG9uGC6ecfPqpbCNrBPWlHVQG1Z7sXnrACtmQdOwNFpeKCWRqqLUhqoLUMilorUgBtCKVBO5ZVJJlCymg+A9LWZKzKQY0d5LN0FZ4iKnzBIXuq6DlsTtUyJWC8g0U8CK8HI8viaVI8qxZttpmgksKVJbIecjmIqyGmU82nghM5uAbgbVHjpccjWRrDiMXAVC11qjxoRGRoNNN6ou99lzVQlkUx6WbX2AFWrLksFEwViDVpq+24r+yhucNzhnMKrS0kwIAeeDOFCrIseM9R1uGLCbDap3FJNJKpFXqN1xf6DMhZwbkYLpHGdmQ77aQwf+bUt4w9Jfvkm6LVSdWOINblA8/e53yW3N3/t9v/Df0GqtCdrFSYyL9T1KW0pZPcdrAau0oTXBqZScqWSUMhL0CWgiqjQUkiTQdKNQKEiKeqqWZjcYH3DWEPpB8rZKkYT2uJBTYTxOjIcjANqeYfodrd5wbuDpWeXyyRnFD/DuI6rdcvlkS1F7lusjrUBpCEfpVEZ8A1fyq7cWTrZroFYNeEqWN71a2SjzuKfViu8HUlpQRuN8II+F648+Is9HtNW4TU+1C003XLcKIJ0RYKAyKKOpNaKdApXptgOHm89pueFUT4sy+zfe0ExdeQTS8tTaoK1dM7+g5IxSehUv51WPszIs2lq+pUjJ0ipUxsgD3hisC/danlIKpcjsFFjHaG2FQknC7WkGKpoiu37t4c+e1ZfE3K7rSa1QjSIXEb85bVEx46qQW7OdMI81/iygJN6IqqEZQ11b6rZKHll1GjpH0o1sFYuG43wg5UgzmqVEmjMUZzC7c+YCt3c37Kcbop6Z1J4SNJ0/Q7dCGSpxmvj81y+5KTs++uDXTMc9umt4Z2n7Qh4Lw06zHSzkRcJQdaCp8Pt+qX+n6xSKm1PEOkfJkWF3zuHmemVogUWji4gfc0nEslCadPJIGe8CLa0hk8aJkY6I1hXvHc4bjK3S8dWKmGaaVmA0RVVKMxwOkWWpgpZIWThbZiWir5t7a2I+SHFhjgupSpGz5MQcZ+LqNjLGosU7Rr87Zzze3ce89JsdznUAjMc7YlwkVNQYfL+REfYX29iDXfLMENRFThKW3JrgNMRlt9LvtZJYHOuQzGfLMo1AW8GtmjgdkQBou+oXpSB0XsSvCug2W7rNln67w/cDYdjIz9MK6x1x2jPd3dGKpsRGK1BToaZKVVCC7OdmdXtOKTHNmvFmj929CW9Y8rZHbz03L6/RpsN0musXv8ENBqVPsT0P/ML9fZYSzamxK9m8ZOqaHWl9QGvNuH9NWmZySvLMvB/Jy1rGwzrx8MzHPVY56lKxBFoCrQM2bGWUXSNGaWGbJVAtULMc7I05SVcsYTgjTpnlqDjcjoz7O5TK7B4NPHn6iK1pvPPWm2y8gTrj+kBTJ0PRNx/p8tU1PGuApjEOhUXrgFIS8S6VYCT4QL/dCpnXSlhfXibm24l4HLl85012l0+Iccb0krje6goJXPUyra26GorE2RuN8YbubMfdy8/Yv3iFxuB8QBuNtmC8pVbp+khuj6ZR5OtfEjSDtAi1NhKAWQpt3ZiVRkJKa70Xs54eGKzp51rbFShovrDzrdTfLxLS62/RgL889nqI6xSUWlJaoVeOqhpLmunOLnCuo8aIruC0FffbNvDGD/8Q2wtAcD7uKUhxSykE4zGl4ZQmGCOYgtoIfoPVXlgvNMbxjtQyNViiLrjzwMWzLU/efIprML+6xbYdVW1YXh9R08j5j7+PNxYOjlu7o+AIvqd/4xE1L7zx+Du8+PXnLMcNg34HnQdKMxTNPWrh27JqET2OFPkFF7wcLqzwTVpV9J3YX1FQVaW2QooTbr0H7sdNAkLCeUs3eLphEP2TUXSbDjF4ZcJmwFiNtorWspzuTCAXRNCOoQ8D7tSNXd2RJwdo05rSGsoFYs5o56lKUVoTweySsCZAM9QKGMvdzUtxmk3TahpouL4XoTtNuk2sAZffgmt8ooPfX1v1xb6GUvh+AEQSYIwUQDkJPkB4OeK886GXbkERrWUrhZbzmp+10HLCh4Dzjn7YMGzPaCVTSlyNKwnnA77rCcOONGfyIo5La72Mip1DdxZjFc5ojDLEWNm/HtluzlmmQjWRaVxw3vL6N8+Jx4gNjqYhtxlU+S1e2rd5tXVUVddIJPlcu4/fsS4QwoBznuVwR02J5biXDmurdNsz6aza0/ixUtKRlu9wLtP1Cmsz1iacXTDqyLBRWLNQ8h1KRaCQlij4FuPlVzTGDNA6wuYSv7sQs0mN1OMVHQuDrvQa4u011jvpPsaFu6vP7/Mrv6n1O8nS0ka6MEoFyctZq08XHNY6QjDkHIlxJGw2GOlyMx8XHr39DsN5IOfKPM5s1YZWy8rPAZTMenPM0mJXhZwLylSMDfjeYXTPMi2ShtwCxjtOlL/WpHOjrZGuSqmrfiGsc1ARK7ZaKHkFJjpDqxmMpG+L+0o+ShFHmjhXZNxRa8Y6sfPV09+nDGrlIght9otcLaX1g7als2ajyQmyYX3geHuNdh21FubjHr1Cz3zoqVlO4cfrO46vDox3B1RxIlLOiVwz3nc415PGBVUzrmlqzMRlwWzPAL0K6xbCsKUAcU3uLnpBtyNdt2Hzxru8fnXD/Okth/kGTOR7/+DH1AzPnz9nGN4WHsWmpw8DqVXpLphKNpZ/92//kq3vcYPHXm5ppqJpyK3ysLfW0yiyNfDdQIoTOSYZU5XM5vwx82GPf3SJtYbaFpZ5RFmzjjW6VcQ4YYxeR1/i3tFaY61FNc14+5o0TeTgsarRcpbDi1IiUmyIyNl2aKugVaz3q7ZjuT9EtSpE2VpE96GUuEpyjJTWCMOOZToQQk/Lmbokcp3R3mO7ngB0/RarkeBQLUyaVBKlNWzXM017yRk7wUQf+DrpCE/ijoagQRSGkpIEq6bEPO4lIHT9ni/G79Id8kE0kyktEvDYxKwgOADRHtaqsP2A0o1SBDEQXEDO0ZVaM2DxvienhdD1QGOZ9qIL67ZoX8nLjK6K3eO3ePGTXzGcGeJ8RL0+kO4cu80WSqNExUJinMUJ2jAPTv/4/3ed9KOCQRG2Wy0F6/zqJJZ9WNUq7kZjWcajmA10RWtHigsbO5DmO1zoqS1hvTgjg+tQ48lZCdYbyBOKBesM2jRIoJQnThOu90ijQJxg07intEJpidoiqkRe/vpjLt97F68l66sYh7IdcUmcXV4yH/ZMhz3f5L76O3m3tLUfXEqk5BnjDC44nNcoU2g1kZYJ13Uoo9cgT1DWEM4HsFF4AGPCaY+1gfmwB9VwwcuNozRpSdQmlM84R9KSSEuiGTCdwXhDiZE6J3Sx5DmitQgrlVojJ1q+54qUku6LEJSI/bSysqm2QmlFxmglcpovnoLb6jrPbLV+oc1Z35Snwkgsmm3tBEnX5/Q9fMOtvK9rtVaZDrdY5+m6Lc4G2XS1wvggk+G+obxD5x2f/J+/pMwaek0uk7hmUJK5VitlTZevWU4xYbNDaUNcZuJ0JPgOHwasDyzzKB2fOXN7qLz45Dnz4U6SlUPkrbcueefH/5jUB+YPX/D40Zsc40uGPuPMjMMQk8L6DbmOPPrDJ7z54+/w/X/2j3n3+98DlVFU9LfCsaxWvEK5b4mXlDDeAhJqa1yQAtN6MJpmFM0qaitYY+msYx73LGkBa8mtUJUilYS2DoXh+PqW8WaPcxtqyqgGXeggRcgR28AqjXeK0DWcqxgnrKMlzhJNovUaKCsd21rlkJLGkeVwQCvDsHl0Hw2TU8L5AWcDrTSM62hKDhVxnlBViq7WKssykXNiWUZSWpimgySr/74vz9ewWmuENRRUyLsF4/y9i+fUpW618f+w9549ll1Zmt6z7THXhMmMNGQZslz3dPU0WjP9QRKgaUAQBOiLIED/Qn9TgDTTao1po+mqLlbRM22Ya47ZVh/WuZFsM1IBxSGbydkAmUESjMw4556z117rfZ83TIMwdKx0e0pO5BDwbX//7lILY8z5ZuEfWcFwLC6eugAmRecxLp10jfMeRSGnGW0K/XaNrhE1TShdyKagnKM1PXevP2b7B0/QG0vNLTUZEpXiKrVqaml58L0fUpWF6qCat/Le/f1Vcl6SxcXZmBc+lhSjlXk4UnOGWknzTA4SNXGCCBrn5aCYk0wqmha0p9CTk2e8m2E0cFSE68R8U4j7Cslh7RpjWnI8Mecsw+6WnBLHuzvCfKDbOLQ75X111NBRkmX98CFoyCFSU6VmgzEtNReabsUpc/PrWr9jwSMPSyl1yaPRuKZbRjlIhkpJ5Ch6FeOMpIQXzbQXMaH2ENJIzoE4B0rQONeKE6AomvaMkio5RmIMoB22WQmlN2ZKXqiiTtGuW6xTpDAxH49QkEDBUtHKYIzHulZOM6q+sR4XxIW1vPgpGTIY7agFcj4JjEVkrJRFG0+YwjInlRC3vKTRaruMrpwo5/Xi5BI+zzJCK6dd9Nv3uKpFeM3S+zDGyelvOqC1ptucyRwZGMeBw2FHiCPdZkvbbckRSq5szh9KqKFWxDiBqVSdZJO1Wk4MabG3pgV5HyI2V2oqzGEihUiYMrf7idyuqZ3Hrz3rhz3d1RpbYf78OTjPkyfvMT77lKJmTM2EOKBCYqVb5jJAPnJ2oek2hVJuUESomlrlNPM2LLGl68VmKl0rbSzT8Yi1DTkl7q6fc3P9gv3dDTEErGslrX6aMbrSreTgkiqEXElFk2PmeLuDbGlsx3Z9RtdvcK6DaiRLbnGIUQvKKDlIlIjK4oxU2lKrJCbP08hwPDAeD+Lwa3rQi17MWVSNmJppfYNRkqSea15EzxXftDjXcjzsiEDRWp79ciI9y4ZtrRTcb9VgZDGA5oX9ZY3FVIXVDWlOKOtx7QqJ+HFoBbZpFotzRqsFp+Ea0XO5BqPFlJGCaK6m4Q5qkq6eFuh503byvq0V1/YoY6lGM4Yd6Eo47CBm8hTQiIFlLgPRVvxZRxlHwvFAXisKAVc3rM42HOeJbA3GOWIthJKWz4l8Vt6iO/efWDIdSCGSYiRHOUhrreRAZhTWybAmhFkyIVko5jmRk7iDu/Wa6bAXjh0WheP22XMOr66JYxDXW6n02wco7SlZM+4n5qEQJoMya6rS+NVqya2LtOs1/fYMTMJ2Gte1nF29jzYbuvVDqJkwHNndvFpYQhLwu79+xTwOC9Hm67uDX0F4KKSQ8O0KZZyMdHKU2WHJKAVhymjfkNMkKpxYGV5PIjB2jrC/pSII+utnL+nPPM5b5v0RkkUrT1YjVVeqqrRdRw4BUqbWim97CgGtK8YrXLsmTGK9BSnCZJvWOL+ipAljtWT3JGnjOt8KFp8CVWHRkBXjOMnmYB15HsUxZsWNIAh96UgobeT0pPXpObz/+tRlVqjFTVZENX+KEv5WFT3iYqsLGbPWpXulMtVYSkz3p8X7EMlUiCmg7R3teoUaW1btlpoilUwuCdt1oIWsnVMhxopFi2ZKJ4yCmpcLOWdinjHtijIFSphpOofuPbe7V2j1EN+dMadC3B3Qu4H1D99jd/OM1ndo1VCTJqnMmeu4LA2/2j2jsVvW/Uqs10U6O8postaY+i0XmcsUUgT8KFQBbx05RlKO5GRk7IrCb7akMGMqpDAz7Y+MKdM0Hf3KoXSlVEMtmpQy436g7XvW51cwRXTJaDJVW+YQUAWUcdQiImkoMt4qGW89OksRprXjOB/lme5EPFkWQnTOMMeA7xzKVBRyYjRoXNsyjUdB6ntPChMlJUqI5AJzqRRtaJ2XFG9lMI0jTAFSQlUZ57wt6/STlJoF01EKXllSyIxzwK/WOKdJ81GKPt8yloRvNky7OyyWoh1owzyNtO2KsqAlcpLPjmsM1onmEVOWUWWlJiWHXSCmSDYV7RW92cKUmO6OFK2JoWJXjuodm4tLdLH8+s/+DT/4/T/C0BHuntOfrSntEWPXrM6vZHNvLePuCKqglLiT3u61BDgpRU4V324wOmGdFf1kihitcc4R5vGei2V9A8bQrLfMw0CYbmlXHePhdvl+kTzPbDYdbd8T54Ht1RnT8RZtBppNollt8MFy9/qalDLdZkW/6ZbMron1xi/vDOFvxTJjjKcqzavnn9B2jhJnxuMO160oZHI60LaWITiGu/0SDfL1rd+5w6O08Cy0MVCzmHhPSa6+FSaAlodPa4dGxkDTsKNpWmqqWNuzuXyAqom426GqwnU9tu0kNM03NKsN3WqNVRVNxhlF0zh8I3lNOWbZYF0jkQ4ajLOkOHO4fUWYhiW0U065Qq08kWMVcZ7IOTKNB0IY78nKWmsJH3QSaqhMWaIsDLZxYhP0jeDptaIsTgil1d+J1zjZ2Fnw7ff//C1cJ2RCVRBjQFuHbVoUlXF/x7i/WwJkxRbbtlusatBV46wI2GuZ0aaS00DT91QU8zARxgRVnARFQdYVvCPUhHKSzF2NpLT3TU93ds7Z5RUb19Lj8LYh5YS2nnh7YHjxiv7BU/x6y6/+47/hyY/ep3cO5TpqVpSUiQSMKrRtz93uyGFMHIZAVcL50PXbe6/+/hKyvHw+c61UtIAb25Z53CEnR8tm1dM6OL84p1911Jo47K853O443h3ZX1+zv3nJuH/F+mJN21sKM7oxDNOOOc7EXFGLO9K3vQAdnZfPfik46+m7Nc44dBW2jqqVdrURceUJfqgN1hqaxuKcpV1vwXjmWIkZpoUKLaHBiVqz8J3ajlozcR5RShPmmVxEJK8WNH99KzsEsknmlEXonwtFV1KdQWdyCVStUL4DJQGsFGEm+bYnn7KYjGQGTvNA1jCT0d5R5gmtDDmJxq4A1juMqtLp6XsgY7S4/UzWhOGItpb+4pJUE85pxmevYHRsy5pX/8dn7F8ObH/8kHITUE1DjRMxjNglgLgeJuo4k47DGxuzejvHkf9gVRlLTsc9cZ4XJ5ZMFrRx97ISrQ2uaUUekKJwkqyhXXVUEuePHjMeXuNbz/rigna1wjqHtobh7lq6qb5BW01OA65r2D644OzqAWk8Ml3fYIuic57GKnSaaKioMKNjwlnLzbPfMAzPMZ0mpEIqhW57JjDTXNFV3zu0vu6R1u/Y4anUKvwbqe4DLC4kaqbUSkoZ1/XUGlGqopQjTiIMVrqSpoizLaZ19GuhHjftCmVhPozcvX5GG7b4zQqzOGa8s+QayWFGe+H8hBiYQ8I2rdhknZYQxKbDuEKYRmKMaCOWWaGrIt0IrcQppEQMpheLK7VSopIgRC+2eNCS0ruIASWpj2VcZe/7NZKKXu5n37VWSi1Cvczf/m7Bm1NkIUR5AY6HA8439OstMcwYpYjTiMPS+p6YJ9I80XUd4/GWtusJ88DZ+SXDcYBUqVHhrBXqq9bMcUY3XiBVKFKtxBSAQtjdUHwjuh4UrXEMtiFQpFCeM05ZuouHvPjkN+A0q4dn1AqD9uRpJDk4VEXbeIzR3N7d0p9dEpUnk4URoQpfR87Lf9b1pV2hlMycMhQByknekcN3DePxjul4YH2xwTjDPOzQxnPx5Cnj8UicJlS1oCpN1+D1EhujExAoCnTXMM4jzjU0zmO1GAbmo8RWiM7DUstAOQzUEHFOdENtvyEuL2rn24U9Iv+/0YbV2YU8YypRjSdXRU4B14hgUymkpZ9mtLK0bYc1MtYep+GeaA2JLAAAIABJREFUhA5gnKeEb/mz+A/WYnFVLNqcia5dUVVGq4o1BXQhJcmiso0gIyiQZtF7NOsNKYxoK06reR6Z5iPGN5QccSfnanXovADqtKYwU3IihAGUHOwUBu97qs6kksglYvuWzq9ZnW9IJvD5X/ySFx98ws/+l/8WdW45/oeX6F5MDaEoGuMYTGF8eUf77rsQy/0I8i2gCfx2S4kcwjUt4+4lSp3hmoZ5HNHGkaIYZ3Kc7/cXoS8r2XeN0NN926DN9xj3O9bbB6R5pBbhzYlRqJJ0WnAQR9BGXFdkLt99j5vPnnHz6o6zqytimrBNSw4zJiv8aktRltvnH/Hkxz8jp0gIhXZ7Sa1ZjCwVYhgBc68X+zq7PF8Jh+ckgjTLhdFLuFxOCdf0aKexvkVVjVaO4e6G/vycWpPkGIXCHEfWD86k5bycCpvVmvXl1ZvNNWc0hhQTuRQKihhFeKyNp2KJaRm31JP93OB8S9Nv0MZx3N0w7G853L5iHo+cAkU5MSs01JrJOYh7xBqc91KwlLScOiUn695tpRTKGMl3unc8wD2fKOeFkqnvKbd8i/OZvtzhKVVOEsYJTbtpe5n7WydYe2PJ85EyHWiaBmss434PWaOUpxbF8fYOY0RU167WpGnCOH8fepfCLCdF7Ui1SrdHG7arc7TRxDLhnIUYxV7ctGjTkPZ7zh49RGnF61/8R9798R9yDEfSeKDkmd531JSJrSNOgtNfbbeMxz05VyoiilVvgcD8NFkFYUwVQDkvLKSUCfORdtWzffiIYXdgGmeM70WcoSpKF8Ssk7Fth2t7jPNicVaK1nV07VpcXDXTbddAYjzcMu5vuXv1DLXou86vntKfXdButri2o9uc0W7ORIx5Go2Ueh9AGaaBUqEqwzzOhFlclqdukTJeImWMlVgMBU3boA0cr1/gnRe9kjKoppVxaxJh7tu3FAIy1YvLzVBSASUC367raFtHGO8oZaLUKEwe01ATYjN2drEuizuu6STw2WpLu15hGod2VvhixmGqQWUwyqGUpRTp1hrl8KYlTkHe0c6jjEIbzRB3sAq0reOzDz/m5//rf0+93ENyzLuBzdOHzGrE6GaBZUpO3+tPP6FmvlTAf/ufzd9uqXsJxObiiumwJ4yjQG6Nv/88izHhjatYnajLCFMnzgGlLXGeFwbdzHS8E92Vb9nf3JBTJYVMKdKlT3EmxYkCtA+eMGd4+eIVh2Nit0/s9zOYhmb1kBeffcL24VP6jeTpzYeZpllDrYQ4oJ0XU8GS9fUtG2nBKXOqlCwq/SVAM8UAC4W4aiUtjwL7ly+E4aIyw3hLiJE5VlINtNuOkiLT8SjiK2NxbSdZMCmQc6GgSakKv8N6YoEYRFxaqiblSq5QcryvKUTn0+HbjtX2gm69pVufLRRlac3O45F7kYOS4kZ+FrHRGuPIqSwiaUSDs5BJ0wIulEJAflO1jMNOXxshsxHD9AYI9i1e98qjZawV5nFx1khLlIUR0fZrur5le76lhpFpd0cYZrReEcaCtRuG3eENNp1ETjN1sVxqbbDK4IpCpUqulVASJSW8ddSamOpM0YIgUI0nW820P7BabVhfnXG8eUb84hV9c8YwT4R5wKpK7xtqigwlEWMhhYnziw1Wn96o+v6vb295+g/XG32ZiEvlRhZSnPBtjzaOzz/5hNvbPaY/I5VCnAd8YzFOI+ImscqWlDHK05gVje6lXa1Bkek66bTO05F2tZWOSk7yWcmJQiWWRFHI6Z8qfC3nOYUSn2BrKRXudgeOx4Ewz6R5oMSJmgMoI8aJIqwgRYGacd7RtB3xeJQg4JwosNDS81ta8MCpvK1VAKvzcCROBe/WWO0kqqVzWAfKQk4B30hquTGOUqUTE+YRhaLxHQ6DSfLeCnUmxIl5PFBDonU9OhtIBmt7jFvR9hdY1UHRNKutHEyRzbiECdtWus1jjr/OPPrhD2l+3OH7M3heWF9ekRnZx1viGAipEnPh0Y/+ANOtyEBd0Bh8Z/LSZZ0cif3mnHG/w3nRp57ik+wCgj1FUKBAa0/JkOZEjhVVLbJVF4yzNP2KGGaUMljXonWDcxuM6VBK2FZKWcJ4Dfk15w9WNB5qnCjzRMlwnCO3tzuGY+Di8ftLhEwHUVHjAtrVijlOTPNICtM3kif5O4uWT0VFjgHj5ELnnDjNEyugiuTvzMcjpRba9QbtLUU15KwWvU2D0hrbOl588jGXP/ge1mi0LZgMYY4o1xCD2JVLBWM01vekacRaC3FeIFrS0qsxorXDOOGF1CoZM9Y3QMFYof1a52Rfq1BKvG+XqgUkaIwlpETJaiGTshQ78v0UImquLFWr+RLhsrIweKT5evqzyeZ+emi/TeuNClstEthSMwWD1nKSLilirTgBnG8wyjCPO5TRdH4L1TAPA7kUUk6kOKK1oWt7qrdgFvx9HKTtbhxljtQykb0VUfphYA4R51tySaQyYcwa71fMxz13z5/zk/d+DB6uP/qQpz/4PXEzVEtMia7r6BrPXU2Mhz2mGnTWdFvPixKoLNyY+q0fZn1pqftfS4XG99SYidMBbxopwkvi/OEVr19khjHiWhkl5ThTqXTrNXGY8L4n5UJJhWm/Z+7EETeNB5SSEVIaj9SUWJ9d4HxLDIMUHDlRKGjr790lpSQ5PETpFjZdR06RHDLaWuI0sF5vmcOBMCe8b2ibnqgUIQeUqsQQ8d5jfEsYB7TTrC6fEA4HalV07ZqcChVLLqJfYoGavl1L3ilKGcZBUA5hf8dwG7G24DuHdm5xoWrQGeMretYCXg0jGI1tG/k6J6xxch2tRzU9ZBiuryGJO1PVTM0VRiNOuZLvE7r9vIakOB5vca3Dtx7TG0xa8+Lf/jse/Y/v8Pr2Ux6kH/Lir/8C9dihZi+kfq3Bwd3zV2zO1gKdvc8fLHyHgiXupxG5JmzXsjYPOdy8ZPPgKQUDulCQbCuttNSCuQpYk4qxsslpbei6C3Em61P2FoJwUIY4zdJVq3Dc72jaHmMajI7kvMeZLf5sQ5yDSED8iuOc+eD/+be8+5Ofo7UjRS3RQccdc2/RDny/Ioa8dHUS91qQr3Ha8Ttnab1h8GSsk3bxKU3cWIPRGqJi3h8J84RfrzHeSOho1XRdi9MZQqFERbPtOdwcOLwaFjfInqazWOWoMVPJCzZbUbNcMNdKKJomo+JMCbPk/uiGmsXOV4tAm1KaSSmRomiMXNvg2wZVKxqFNVZs57Yl1yoMgZJJqciLUYmT5XQS1fZLpGYlEYRmCRM95U2dTlv1S5TMb/dzqlF1yUDBUIojJAe6lVyXWkhlJsSBUgvDNJGUQVmPsRrbavza0VyesXn8hG69Zb67QxeNMQ12taaeBMrKkNFU10jgbJxQSVFMy1gqcZ6wOWPaFru9ZL6def2Lv2X16IojB8Jx4PbFa9p338H6whrH7mZHmKN8HnSkUYZsG+J+JoxHcs5UbeQUeZ8V97YsBUVRE5SwOAyNJcyzjDNUxTDj21YiHQ53OG2w1pMXirEpoKYIFcZ5wDUt7XqNaRsymnlKxKQo1dKuz7DeUqsQfSsQcyKVLMz6mslJ4maMNdiFjo6q+K5DG8V0uKVxis4mutbhmmahRGsUBes1Td9i25ZqLHPMZNMQMQQMQwgo32KVxekG112SkqIqvxQ93/Q9+SrX4p88vV+sw23OuHznCZvLM/qzK5TeMO4S002kTI6UI9VOqEZTi8HaFussqYjeKuckJpLVGgKE1zPxAKvVJVfvvEv38JLV0ye0FxvWF+esNmt819CfbVhfPUBZTU0VT0/YDUzDgGXLZ3/xl5jHif6njzDjmuu/+IB+26PMjHU9XVmLjk5PMCqKC8LyqVos1HDyin5zl/trW2oZA2WOwx1zGqgq4FcNr59/RKoV1TSkmqWYNRZrLDpXybBUilICCmGLWesJ04T1ErmijYwolVbkOFIJ999/nndYo1AYcvakYpljJOlA0jv6qw37m1d0fcf2/Izd88+5e3HDPEb6B2uwmVzTMkDRlMVdvbSJv9ar+DuTlk8EyFpOYZzcXziWHypMR8nrOTsXG/okdsicC5RKoWCMZ55GMAbvWnbPnrFav0N/8XCxrEfCONO0PTHMlMXaTRXScc7LC3XpsJwSzp31b65rrZKovdChFaJ8F2y35G2lNAtB1HvieKTxksyeYrgXUUq7UC8/96mDszixlHqTnr5k9JSFzlwrQr68T13/9j+oCmkvpxgwSlxqChndWSsPEzmjleg/ooJaogQUxgPe95xfPeagFNdffMrq4iHjIdCsOihZ+D7zkRxnnIWSA4fxBtefoboG1zpU20K7JWe4efkJq8cPiRvHtN6yezYwugIb0NPIdHdkrTbEnAkxoH1D1Y6SDS+un7FSKyp+IXVnKvFL9te3ZGdc4k5SSpzkZjUvI2mtqaXQdB3z4Q7QxHnGdh0xzqSU6ddnlJBIccI0HoNlHA+kMjMMe6o1uH4NZFIVpIBW6h7kqZWjloxb8ri0kt8zZUlrpgp3y1hHihHfrcURSKXvtqQYCSEQUpAXfK7opsVaRY6BEtMSZTxJEnjfspsOEkY8z7z65V+xffBI4hPeklv6j63TgSvFmWALxRQgYlrPZvWQ6Xjg8OozLp48ROWC1dKJbddORlG2pcaAMopcE4kZf+YxCUwj8S+1DOQ6QZFnPee4wFjd0j0rZB9RjyDbCZsa2mZLudH8+s//jD/+3/5n6Sa9OufgbikPJ+YbUMliVMW6CsXSNA0p5C9F8ryV9rrfatUidPhaEk3bY/2Ku+vnbB8+RitPzYL7oGa01ZQwYo0cVnIuKFvQrSceDIoOayQPUluFMoo0Z7RpsQaUUcQpoF0kB4XWa4zV1DygasD6NePdDYcXn/CDf/bPOV5/zu7lF6w2V/TbM5IOzMMO33VY3xKmIykEvqmb9zsXPKexTK2VMA64tpXsm0XMm8JMmAf6s/N7SJ/SlpSSwAqtFE0xiubGes96uyXNkd3L13SbDRhNqRMpzvIidF7seNbc82BAAGqmkaTnU6p5LgnjlmKqVlGGl0JBChHr/BKHIeJblkDRnKRAEaGxFDtiwX/Trak1v3GlLcWLuEDUfdEFi4ZHa8IwvBlv3c+gv91L3KEStFpTpF89Is57iQIwht3NSzbdipLiEhqZwEjoaJwOZF2ZU+T8wSNG17G/uSGmIA6PGFit1zgN6/M1XdejjecwTrx6+Yzj3YGL9imb83eZhyPXn31AaxUX736PqSnE6Pn4z/8vrn7vPbKbOe5Hom3AakKehU6qCtUUSquJVnPzegeulSKZDKq8GU++TatyLw6WgEmxLysnLyKjZXyrrJfuaSn4xjMMo/CWSAzHO/xmC1EiCEI4EuIMWhPCCGSUlrEGWZw82nkJEFaFHIJY0o1gLEIO4oQscmgqKS9xCA0xzxRlaHLFVivJ66qSFVhjqblgrKWmtBxOPOvVGblUctYcdnvGw8Dty2c8fPd9oaC/7RumSDgI04hrwLWN4DmolDigW8Nl84g0DLTrDUlnSpmoeEqsGC0REsZKt6fqQlGJauBwuCFZR9+tSCESydji8G2/6K+iRIr4Hk0iqgPaG5xdYVLHp//+L/nxf/UnlDmg4prp9hUX7z/h5fVf4dsnUB05H3GNp0bPuL/G7y3Uk8i1focsWl9eCnJFGYUxDooc/Dfnlxyvr2najtV2Q45H0KAMNL6Rwt+0FDLj8UDFMR0PbC+uSOmwhF4nfGeJc4La45w4kp0bmYYB36whHqkYyUCzD0iT4+Nf/jXv/8EfYy2o1tO//2NyKKDVAgcWMPFJTE/VfFM5Ll+BauhNpV1KvmfPlGXcFKaB7myLcY5cRLimjAV1aksKaA60wMmUxvWW9cUWVTXPPviQEhRkRbda0/QtikIMR1IcSGEghZFa85ds4Ev7r2bpJNRCSRJod0pirqVQlpdjreWelsxCEJ6HYQFt5fsNr5SyEJLrPWwQ5CSll7gJCWeTwk4bs9hD5XunFL+0eb5Fm+iX4jIqFbSiLlquSsW3kkhdVCXXsqTxSreNLB2h+bhDa4VvHA+ePuLq6QOu3rmi7zTr8w7bQygj47gjpoHtw4e4pmV/fcN0vSO9vqMMex698w6NMWzdOemT1+jbPU+fPEYbyL5HbTcEn5lDpGnWnG0eoFOmX2+wfQ++A62XscDpjfp2wc3UImY8fe6pFesalFaURcyrlSDsY4y020uGw26Z+RtiCAz7W7rVFmsMBihpXqJZtOi2jFueteU3LQWK6PnaZbyklaAjUpwli6ek5b2hhH5eFSkmqAqtHArNNI1M8yjjZmUEBKo0RhvicCTNE03b07Zr6hBodUtnW8LtLcwj7//+Hy/BmrxVj+A/tu6t2yUzjyNhHKi1Sjd8GR/azoCW4E7RJIrI2fp22ZTkMJtjRKHF/RgrTXfBcHPAqDWNewDFSCG10NFP8T0ajVctrdniYkeTN0zPRo67F/zoX/1Lpr+548Wf/S3+akK5AbOzKG0oFHIeyDky3oYlG2rm3nZ/EivXt6jz+tuuqqlZQmCdb1C14Lzj7MEVNUeG3fUSG6IJMRDTRC6RnDJKOaxtMEbTtB371y8wxi6vcHkXKO14/fkXxCFBtnTtFTW3oAqmKTTthrZ7wuF15vO//ZTNxQ+wxrK7fiHykpKY40RanuemW1MLTIe9jLO+wUv3lb7JxZ4uoy295OGIgtxRSlwetrQUI7yxTC4iypQT0zyi2wou0p9dcrw58OJXH6GCEXS507jW0m83KF3QpmC9AAAroumQwkfCO9GaGCSQMIcApf49UbIUR9b5ZRRl7gufnJI4RZRYzlmKlS9DA4U5JGLluhw5ZOylF/facnp+q10hLB09udbNekvTr0kp0PRrsa7XhGlb0AprPRaNN+IIkNTfgDaFduWxpmIoeONoui3znNkPM8d5ZiwzxVRSjZw9egdrG64/+g3T4YbNu0+YzETMAX2E67/+a374hz8jTzfobAjJ0maFdpUUEzpDUw1n7Yay32FqpWgW0/bpheqoCFb/bVx1wSvI1/WeHF5zxDctw35PKeC7NdRM262Jw0hNhbbppfNjLd44jDJ03RqrDKSE1QarZUTdNj2tb3HKolOhhoBGCeRMi5HAeEERaOOpVRGmSQ4duWCUwSrHnCO7+cCYAqSCqwatNGmeUMipN4dAioGkNCEXQgrEOPDkRz8hl+n+Ofy2OyV/+6WoizunxgoZSsyUlJjTiO5XHA5Hco2szjakeRatY52El6bkwEmANE1477Basd5ckKcRq0TT16w2C55DDB2FQqojVU+Youj1GXrSfPo3/4Hv/ckfkS4iZ9//MWZqKHompgETNLaFUiesr2hVmPcJ7ztqtcLCeOMR5W19Lv+/l6KkQppm4nik5EiOE84pVts1Tddx8/wzUqwo25NqIZYo3do5YTA01rK9vARduXn+6TLJqORUMF5x9nTLPD3ncPMJty8/JMSBGGE+OPYvLR/837/h+YcfcfWDh1y8s2U47CloYopM04RqWorS5JSxvkNrR8mVFMTQ9E2tr7TgqbWSUgIl7qwwjVLdIdqOU7ejLHwAgSJxH1dfi9i/lTakMuFXnkff/z5hPPL6k09JIWMaSyoTuYaloFlyqu5T2kXwaJxBa7XQkCVrxDiDWQLtUGrh/TgJMdNGOlLjRJzne10Oi3DVaEHhn3Q62tglk0sKJ5RsHKdiT2Ik6nKylQ4Tb+No5H4pqoJxGgRGmQrO9fTrS47DgYQipYhzDpWTBHKGRDoO1Bhp+tUiEBc7bAyZGCvzVJiC4jAUxgTZWnTf49drmtUW324I08jZ1QPMas3UeSKFF7/4FZvzMx7//CfyfScpXJtcUHGi7ztKnMn7HYwTNkOcJ778MlX33Z2vlxXxdS7pOGoZ5RYIIRBDEmhn2xLjzBwCzvfEcWS6u2YedkI9N5q2aQVDoAw5FVTVGJb4AdOQ50CeRFdDkewmqy1mKWRQWkZeSknOXH0zYhsPO9r1mRRFCKXb+IZiNDiDMQazdBKNdTjfijbPOuYYGXNhLpXnzz6mvXzA/njDYf96wUJ8mZf19q+cCnGK0i3TBq0McQwUpSgG3GrFNIwo5XF+Q84ZjCbXRJwDRjtU1hLEmidYUtOn/TW6FrxrMNovjByFcx3WNBINYhT5EHn90ce8fPFrJo48+Ol7vN49JzQJ5WEeZsIYaS8v6c5WlDgwjyO+Pef15x9h+h510tHdC12/TJf67qzTxCDncu80lJSAHaUEjNFsLx8xDyPGdlRliVnGziCZj2VOlBRoNyu67SXH2wPW9tKAqHt8c2B1YVhfrnn3Z3/AOz/+Ob65Yvcq8/kHH3H++F3+2X/zX7O5sih7ZBwP2KZjXtzUcmSsyx5vZACAHGy/ydbqV6DhebMKinmaMV4spco0VGWoqaCqFeKjraicSFnEcGKFFdGkxqCyQpseaiTlHd1Fi199n5cfPuPjX/yKxz/5Hr7rmIcZ7VbUmkScpZXAx6wVB5hSIjotgZIm2n5DiYFSQbsWgmRiKS0I9hQiMQSMa8W1pYTrUpXMS3WpFLVsgEpOMWLA0vcBpCiFslZ86ynLdrkUdmmevqmx5de2ElBS4eWnn9E4T2M9Id2x3+/pzteYkrBG0rJzTlilcV2H9p4QZ8bxiLKiwfJaEWuSDpk3mGyoSmPbLcZoSky8/PhXeL/FbnqsTRQ2TFnRJnj5y1/y0z/9E/bDa8ZjwrgeQyBVWLkGu9kQbl/T9WtygTgNJOqSqyRrGWR+Q1fz61lqmakr7THWMk8D2np5dmrFdSv2N6/wV4/RNORwYLXtMU5R8iTC4hKJsWBsQ56nJfcnMFPQtpPNUytKiqQFnlYwEr7bNJiuRdWKqYYUZ8zKMB33WG8Xom8RM4ESTo+zFk2lpAllKjHNWGMpUejBc4jipKSwP7xkPg6sLx5Tq6JU/bXj7P8prKotCYnlsa6TTonylKSAgW69ZT9oSuwxxpLi8f5AWapsjt534vQplhwK2rb4dcfNF59RqsKtEt32DKVg3B0pMXD9/CVOgwuG7slD7Lnj0nRUU0g7KJ88R/UD2WniiwF98ZgYR2zWTKFHc45qI7lrQeXlEPLdu39fXkpDKZWEJgwTrm3QxqFdQxgH+q7DWcch3CwC8gbTaVABVZJAX7VnDgM4hW1WjIcbfEy0nUcpGZFl1VBqx/XzIy8/+iW765dsHl/we//q57S94nDzOTkUxv1IqQnXtozHPUpprLfidlWCqqi1SqqBWfIj6zdziPxKCx7pahRSEF2M9f7L/1H+Vt7s+koLxVZpQwqzvIh0pZSIsS3zccTbBt9anv7khzz/+BXPfvEpj95/SrvaklPCNpDmTFZmIYYuArtS5ZSpOzKZUhTKtsIyUBq7xEukOTIdd2jj8G2Htm6Bki0K95zEeq6KWOHVaWZc70FaSklulnxvtQj2pOCx1hHmUxv97X5QJe1asAH92UPWq544HOjpmaeBft0t4atGRlvt4uIyFqUU0+1I30rG1ZwzOcw0XY9pPY1yuGrwcwaV2L38TE6RGjCK28OInm6xzSOef3BH+3hN6hXHcOBw3HG27dAh0jhP6zbcHgcO88ReQdUNx2FEYd52Wcc/uqQTKRqzN2RW0Fqx3p5x8/wzSrnCdxvQ0HT90lHNKGXIKaOtQRnQjaHESNN3xByoS/6SvOSKOLWopAIhg50DzoEzYgjo12umaSbHwOrsUjR2RYqvFGZwBq0U3jdM+510eZyjKoWyXn6bGHDdhjAMHO+uuXjyfQlaLGlBZrhv+Ip//atWScxu+jUgrkqtHTUJd7u6RH+2ZZ6ucb7leLtn3T6QjtCiy1RmcaAu7+2QIt561o8eo7G8fvYF4/GWTMIaQ7/a8r33f4KyCtMHmuaKD//yV7RPeuYcaeuGu+MLVmdbUlc53rxA1xE9Q5xnuvU5z37zC5x3fEcSs367tVyKkiRKSWnJtKSCMQ1xEsdyv7nk7sVztpfn+EaMRNa3zONEKgOutdQ8oc2OzSPH4eYLlP8+jX+HOXrurl/w+Qd/jjWeq6fv8fj99wl1RwyHhdeTKMlQs2GzPaPGjFk6iHkcJUw8C3x2Ho9L97Z+oyEDX2HB80YIKZZkz0nPIkC+vIAI37ST1WKPRbG0xdVCPg7kmHDNOYfbI5uLDa6Dh+884vZF5ebTD3n3p3/M8WZHLkcqiRQL7XorXRskqbvGzLx/JUKqKCdB4XdUakrkFLHO03RrcYUUSRc+kZAlXLKQVcIsY7BTMCpKGD0nuvKJbCnu90Xrs3wdxiPfBZVkqdLR6jZbXONQpqBswlVNd3bFuLvGu4aKAQOxJAl2NNIVq7Wirbt3ueWSqUaIwFor1BDYrB/y6osP2HQrto/e5e76mhgHaveIvh+Jd5UPf/05f/Q//ZyQJmqsWG1xTpLt98cd68vHxFRJruNYYB6PEmxb3/579PfX6fMqz6e+RzaAJGAbY+jXaw63rzh78JicK6UIaDOnxLC/o+lXpBrvT+CFJA6SWiilUnPFGEMpEd9I3o+yHpUVIYiNWVmLWez/03FHv70kRol3qVWE8CiFRg4hw+6Wpu3F2l4SMQRqVRjf4rsNOSfuXj3j8un3xbhQ8kKTfbsPHf/JpURKEOcZt96i7AmloTDKEcYjvusgRlzf48eGmiuubYVerSHlGW20sNBURTeeOU0YC1bD2aPHuK6lUkhhxFmHqYWkDaEf6Jxm//k1j/75U1Ku+EOlWfW4VUsMe5rLc4qRDoReCivnG4IPi1D5v6zTOo1jc4qUXHGNFp5SLvimR6Hw7Yo5TNw+/4KHT76HbTei06kV27YYpSUKhAllDdtHP+T1FzuON6+YDkdMY3jw/R9x9c4TGgsxTQzXO7R+zO7Va2o2qGpwfo1tWqb9HTUlfNNzOOzQngUELO/5U3Og1nLPUfq611dY8Jzw4l3rAAAgAElEQVTonoqaM6a194LgyhsRr7iX7AIClC6IFBBCgayliIBYSdBZON5x9+oLtg8uqCrz5CePefXpxCd/85e07SM5dZoB6wNxHhh2t3JSr0oSk7uWAoThQKFgXYOxFr2QnbXSkoF1H5tcF9eKJ2fJkjlpb9TCmZERgBYUT6n3p2K9bNqiD3ozW80nsbJSb/d+qoTJM88j0+QwugVlsA5KnOhWZ8zDIAnIzqKykJZrShjradseqw2mkXviNhtqLtRYsNpCLLz4+Feszjd052fkMGANPHj0EN01NN0FX/yf/5r1eYNbd8wvjths0b6XTbZx7I4zx9sXHG5vMOdXFKWRVDb1nTxFnkCnJYtj0fpGOpbaUdKMMZV+tebmxXNWF0/x3RatIE4BMFjbST7e7hrfdXjX4Pu1BIpaRwkRSsI4Ky+5knHWUqJ0fIy1KJXJVVEKTIc7iaEwhjiP97l6cZ4wXjozaZpouhXGeZTRlASlKsqiy6ul8uLDX7G+uJK0dsSAwD0O4ru2ThEMRTraasBaDTWhcWht7z/5IUx0bGm6NcebO9p+LUUnMuKnKozxwm9SBdO8AUVqU4nhSCFT4iwj0DxDs6J1T/j8gw/wWw8aTG64+eBX9E9XhDIQbw+4Rw8ECTJmtLaEaWDY3yw25u+O3ur/d90jTZZfT67kHHC2WcC8Ir24ePIu4+2GF588x3cbmvWGdvsQ71t0tcRhj18ZcgkcdnuG3R5jDT/4g/dZX56R0oFSrgkhEWOUkF5lSXNBYTFGCT9rysQ0Qxb93WpzQa6VOA2EaVyQfItZ6BvcB7/SkdZpVYTL0jgvVlYkzJP7F5K86HLIUhTdV351UUxoGY3UI/2Z53gzcf3ZK9ptz/mTxzz98e+zv/73tNsVq/Me5TpynCilkmOlFtHaKCvzZ60UprpFL1S/lGAuD3KOUf7gpzwmZSiL00tCDEGxJGbfu1oKCil6tNZvRJCn7k4VhHcYh/8cl/if5lJLcasNx92eNExcPnyMVgPTcScnx2ZNjBOu66AEjLYL7VMz5T0Og/Va7ptrSKFS5sx8fWA8XHP+ziPcumN39xzXtKQ48vi9H3JzPPDF3yaGV3ve/9M/JBxHnO455AGjgZooIdGdXRHDxObqEXMoqOOMrUp4PKr8HQ3Pd22dnkUApeXAQBGtW7s+4/b1K87Pz5h2NxLdYC1aG4bdLYmEMok8JXzTieC1FKzxmFqxIKJ174VI3jim4YCqDVhLKoqcANtK5taCLwBxQvq+J4SJmhOb84f3iId5HKix0GzPUL7hcHvNvN/z+Ie/J52GGIjzSJYAvO8mugVgOXSWXIjTjN+uqTXhXEOJUsiUBLVaYlSkUKhJunPWNcQ0YJuWNB4EtqqsuFBzAlOoZGpOVA3aii4shiPtZs1q+5jwquezv/rf+emf/gsUHbuPn5PHkWws2mhcdoBHlYkTCmI67BYB+zd86f6Jr5IzmYD1FrRkEZYMRrekWGi2PV26pBbDcDhy8+IzrNc4vyUlxbB7RckD6JF3f/IjLh9eUXMi5dcyCamVWg37mx0X7/6IYXfEd+eUlBjvbtCNw+gOnMM2RqIttCLN82Ik+qeDgfjKC57TZzOFGd8smhmKYPqXE5ZxbrGJz2jn7yGBUNEYaT3rzDwe6VZr2u050y6xvznQvNyxOr/g6r33efXZh6wfvUetcrNTFBdVrhXnG+YwUHWlJol9cNZRVRGo3dK5KadxmzH3DB5A/qxLYVNKxhi92NhPjRr5Waxxy78Qro/c4ILBkEIgzjNv7vbb/eQqJZtlyRVVNLc314y3A+/87PtiVy0Z7QwGxzgOWKPo2pWIzZXBmRZvOwyKmER/cdzdMe9Hzi/f5eq9nzGEa2qcwDeYpifvD5ismF++5Df/7jn/4l/+d/jtDcPdgFEdd8MO5wxnzRodEqRKidBfXhBf36LijNGabKqMKf8JPJRf9zr9yHohlQtPakH3K4VWms35JS+fPSeECde0oOXg0PUbchKchO83OGsYdjeMuyPatTSuQWuF9i3WVXIpGO9w2rLqPEUJzqBaz/Gwp+taOaEau1jUDSi1APMyTb/BLVlNuRa0ESv7HCLjzWtKzmwvrjDaMMfIPA7LY7cE+b5lTKXfdsk5rKLQlFLIOdNvzylzWLozljTN5CmhscDM+uKcV599yNnDx7imp+Qg4ZIYUspARluFdo4csriySqRkhfUrYg2YvufVrz/ho3/9IT/9H/4U/2DChBXjs7/lwZMrdAcqQykBi2OOE8Z2DHe3i2tyYQnVU/L3f1l/Zy1xDTlnLKI/BSGa52UEmfIB7TJhGLDecH71LtYpjvsBHTXri/fxjca3kbZP1HRLPEaqdVAdpThiVLTrx0zH4/0IdB7u8P2a61fPOOu+h7KWUirH4YB3LfM8kWK6l3u8+TN/c/fxqxUt/73NIo4jzWp9nyQu4ywnhURF9BlUCdvMwoUQjQwo48hJkXJL1Rm/NSQir7/4gkKmO2tx156bZ3ecP7wkl1lSYXWi1EBMQbQgWSyZQj6WoqPUij7Z4/Uyflogc0qfwgwzqsooShlN1W4p2OQ0o5XCWick1xhED+RFLW//3/bO9EmO4zzzvzwqq6qv6ZnBACAIkrJFXXaEJa3DsYccjtjYz/tHb8Tu19WuVl5LNuWlIIA45urpo44890NW9wAUZUmUCIJAPRFADGYQjUZVZ9ab7/scRiOTpFmvMhv97a5zBuQRRdZQKBAaU59y+fgRk3unaCOR9Li2I0mDR9JutkhdIYQm9B677WhvnuVxiRToSUE5X6KXS6yGtV9nkntKJKm5vlqj5SmPfv6E68dP+M7ffIxfWGJbooWjLCQLajbWkmaa4BuCLOgw9KsdXdeRdC5GRRJf60L82iBe/UMS4IND+YQpzKErIkVieTzj6vwpJw/e5/j+B9jtNQxuyUEodAqk2FPONOX8lL61pABN19OHzO0TWlMJzdGsQqdAQJGQuVNjW9RsgksB6X02oIuJbrdiMpsBHikSIYVslBgiTdNydX1JWU1YnpySbI/wFlkqnI+gisM6f3chkOhhfJk5k23TIXVFihYhAloUlLWhue5Q0VMflXhnWZ7dZ/3inLKumZ+dYF2HixFdVri+GeTrOlOsUkDoCX3TIEzJ5O77uJ3mn//Hf+N7f/9j9J0WkWraZ89YHi/Z6h3zeErcNJkQ3Xn6xlGUFX3nSOi9Y9q7OYn8N7FXq2UqiAB8B0VVIXTA+46yXuD6SLfeMF3MmZ3OQCR0aej6hkJ5zs7ugZJY19NcrxBuRowF3icKZQjBIlRBb1tmy2P67TVSgt+tOH1wn74TVJM7qMF40ltPFBobBR51e9/S59/714OvZKSVke3Fve2ygkPKYdNJg1sxB56L0kWOZ4zhMBZKg0Ggt5airOi2a3ShIML24jNM8T73Hn7E41/8EjedgowI4XNWjxTE2CMQaF3eOimjcoqvzLLoffrs3h5nvynmjk8+CUkhkTI7wuqiRCoxuFFmlVcccrhMVd+eQFLCD+Zn70ax89tIJGShOH7wkKunT3n4ve8SbMtuc0W9qJBCsZif0K+u2a5XJKkpipq6nnHn/TOC3+J6gdQTrO8J1pKkIInEzc1j5scnoA1PfvEbdPJ89z/9B/R8ymef/oL5fEl0Hi0sdVUQHFRRIkRBXxQ55qLrCSF87vTxjt6sPQSD2lAMBN/si3Vr0JcwlWFz+RxvG6p6gtI11kYcCil0dm2Nlhg8SubXk5M5wQesbfB9j1CGVnlcKEhSopXB9TccLU8I3uNTJPkeLSUiBeazBVIVBFHRNA2CiO16bi6eo8uS+x9+m3o2o92uaPst0/mC1u7wbnB2H/iB7zbEK5/u6APdbstkNsPbhrZrmB0dUcxqXOqR0WReVNgwP5vRtx3bzQpjDIUUlMqQREBpjfMBZAPKUlSKcppQMnL1qx2f/fwXPPyPf83kw/cIsac735Bu1hRnp5S6ZLfdUETw3qKkyDYIlxc5lucl3seIfwt7R+1IcD1JCYQyWbpueyazCWWZObUhRGxr2Vxcsjw5pW+3BBLeW+rFCb5ts1ig0MgIMQhCt2U6PUHEnLe3WV+yOD4GsuCjLCcUUucDTUxDjprM4d5v2J76FRY8uTCwXZeDIPf8gGH8I4QY1Dm3yhAhykO3JXh/KH767YYYPNP5klQbbL+mXV8zP77H/PiI1YsnnH3wMc62JDwpOVShiC4elFUpZafjg919Zt3lNaVuvR2EFGipM/k4RVRhhmI6n4xEIrfuQkCp7BAbvMsteHKhFmOkb3a31wF4FzZcsVc5DQnjkSxT1nLC5mrD7GiJqbMctru5JnrPZDKjuPuAqPK9uDl/yuQ4AR2imEFKVKVCSUGQltZGJuY9yvoBu/Mn9N2K7/7DP+DVGtdbYrKZbI7E2ewKO5WaCkMSji5Fum6DCOOp8fO4XZ/5U+v6HiqF1lkW3G/WzJenSKW4fvEZq/MLimpOOV2SYqIyE2JyiGyHNqybHHIoENSTGe2uxbU9cVYSizldc4NwN5iyptAKmRTBdqQkqKopIliEd3if6CjwQXH55FNMNeXORz/AlJqySPTrS/p2TRKBzjf0XY+QdT6ciAO1bgT7ZrbAWcvm6oqynlBOjxCFwSyOiARIufA104iSoOsFF5+9IM2WGKNQyYOO+LghKZCqRKqIqSG2Ux79z0ecf/obfviff8Ls+2fcND21P2b9618zPznCyo7gYbddsZicYmOEtsENvKCU0udKtBG/D0lEQkgIadCqottticFTzuZIEUgoQoTN1QuOju9lmoYE225AZXFAUdZEKdnu1lSzB9huxfbigt7sQGaaRzU/ISlJ225RRYX0GkKkKEqE8Ni+x1mXOYFf90X5HL7SDk8CiDlpXJflIck8k37TQcaeL8xevp6Q+wT2IQMrxUg1maGUwrpAvTih267pmob5yR1s27O9uWR6tCRGhzYVIeRYixiyOuPATxjIiwiB1Pm/n/lDt5blewJy9p8IvFKlipyZpQuD1NktNgeJpsGPR9I3u1tl1ht3y796ZKl+LnqSAG1Krp8/R8gCpUu87ZhMSxbzB3jnCCLRdhvKyYTFcoFvA9rM8D4iVEepBfWkZNdccnz2Ed12yeP/8xue/ev/5rt/+22SvMB2DqlLlFDYpqEsp1ld4nv6XlDIitA7dk1DSjkra1R+vIpXnIcPbukdqcxrROqCQhdIpTg6fQ/nArvtms3VZwiRaG6eM1vcYb48zeq8EpSKg2w8e/yc3HtAu92xvXxO3/foUjNbLNEiK89936OloDo+heARssy+WEnhesfFk//HyXsPWd59D4BoG7rNmr7vSEKgiwohDcjbZO23Mvz1T8ArnR4gxIDre2KwmNJAdGhZEoNDxoDSkmAdk8UxlxfPmJ+cQmUwU4MgYKYVRi1JTcXN4xs+/V8/ZbqY8nf/9b/Qiwuun9zQiyl+q5maOWFaYIqC1cUVSI2qamZ3Si5ePCZIiUxq5Ot8CQgy/y4IRYodfbNjulxi2212TY+wWW/QZUU5rfH9Dh+yt5xtGwSSqqyR2jCZnXD17CnJOmYn9zClISfGREIU9L5HCE+0PSImZFURvMN2LX7In3wT3cy/woLnFt72edSkdDYfGwzOkkiHVGSkQpBbrUJkubjUBc72KJO9Wbx3JKEIUSLNjNXFBSf3H3L20V/w2Sf/SD2fkqsoiS6m+NjfdopISKUGZ1j/SvWZBHnUxcubfhqktBBTQkmN0iY7wSr9km+PH3xL8mgsBk/f7t5BcuTLDqhxKHryr+ihXpywunzO/Y++xbSeEu0KLx03zTX1fI5SUJCYH99h9eI5qp6iCwuFIjjN+koi0kN+9U+fcP74CbPjU773tz9kcSxIvcdtLKbS4CWBQKolUmhIgZt2i9M1oeuwSYDUZF/oEb8LMaZhdCtJKW+K2tTZ9dh5UohopVieLElMEFLSNx3ri3NWz18wO77DZLlgUilECAhy6na3vcI7h5KJulSE5GhW59T1BB9DtpKYT/A2nxJVUaFMjW22rM9/zcOPv5OdZYWlqAyb7RrXtcQIsiiQssR3HhF0jl0a8TuRNRoR51vKepkd0Dcdvm3oRYuzlqqaErxFTyoWpydMzo7puwaCYDH9gGgj62fnPH30M65+8wyl73D8/l0++NEHBOlwfYkRmvhiy/b5JScPP6KLlrjr0EKjyglFOcF1G+QQQQBv2iDkm4BEIg4h1pHoE9V0jhyeuyEJWutJxmDmU9r+imQ9upxTlJPBURuctZmg7ix+Zzk6e4/6aI7rb7D9BqlqUII0hGWnqAh9i64Vfd9gvc2MIjUY9L5hZ43XUvCkmPB9TzkpMu+X3D3xPrcvpVR4Z1FSYSpDtDZ7eAzp40pnx8Y4ZOxE70kRyukRq4sX3P3gI+48/BYvHv2K4/sfIZQmuoBQmmB7CLnDY8piaCzlDk/wgwW9FIdiTEp56AbtR1VSaVISeG8Pfj1ZZp85DmEwaEMIdpubN+4mv17sx1q3l0GoPM4s6glXz39D9eFDpJT0rkVOSwKecjJBR6gKQ1UZqlmNUgXbbcflry/YPbXcPLtifjbjO3/37zi6W9LevECEOSKWqBjRlFTVnM3NJeVCQJHNsCgq1rbPZGfEWx/x8WfB/kCQcsHv+g5T1XgfyFS8RIoOQaAocppKdXLCYvke25sdF08fsbp6xny24M799ymrObvNBcF3zI+XyEQOpJSSJBjk0g0hdOigc1s8ClLoaDfPSd5y9+GHHJ0s6Zo1vtthd3YQPxgg5mKnD7mtjySJ0azu9yFzGyPNekVVVISmpywq0ImiOkLJGWG7BWB99Zj6+Ijl8g5PfvZ/+fS//5T+2lMURxzfv8PHP/wx0/dKurgj6EhnA0LVKDFBbS9ZHh9jTaBAs11fMVncwQvBzYunuO0ud+TEOMj6csgb7j7AOmfbeXRUJGWwncUHKGcLEJEQA0oqggsIrVCqhJitVrr1ht16xfToBG3KIdYl20roVOCDQ08MOTFGkIi0XYO33XDI2DcT3ryx5GspeEQSJA+h9zluIiWSSyghczGiJYUqBsfXCFrnNmt0+fEZ80VNyeUFkbKPjqkmBGs5f/Qpx3cfIuWE62fnnDz4AKUTXbcBBVLqzA0i5U5OChDz68QYEUpngU4kV6xpf8JVxCiQubIheEtRGpJIhDQoyihzvKQw9O2O6CIiynf0iLLvat3yQCCbDSCzB69AcfHsBafvPSSEDcSOGCKyKEkSuijYdZJnP3/M9mbN6uKc+dExJ+/d58Mf3UNNoSinNLsGxITt5gajTe4ElgpRalKpiVqytgFpTijcmtB1JCGJAgT+HS9K/zDsXYlj8IN9vcimY8GRVPbNIip8GykmJbqo8M4zmSs+mP8Fttnx4rMVn/ziEZNZxXRecnz3HmDxrqfQJc62SG0Go8kF3c2K4AuSrtmurrC7C+6cHTOb3888nqbD20i7awY/rQKlDElm+0gX7avNxhG/E9lnVeV9Dmj6nqKukEcnRNmQVO7VmtkUU2ukrmguep4+esLN5TV3/+ovObp7hqkNfbtGFJLOCKzTNDdXiBCp4ozoBWu3Y3nvAUokXNdTlHOCKGjX17i+G3hFb29I72vBITJFkO+cpGssUkpc21BPFqSbLV2w2SsHIKwpq0lOt/ceU2cB0Nm3vsV2dQmiR6DBR8pyQQwRU0hi59FMiCSS8DmYFnWrqvt6rsDvxWspePaswX1elioMKbiBQpGGfJvbClUOzstC5IyQHAjqSVFBGkjIMRKDZbpcsL26YHX+lPnpPfpmx/riKYuzM+rpHOcatDa5QxQcQiSEyg9hkSB5v+e4Zy8dslGiECKrtYRCapUDCk2JKspbczYxKLVCYLe+xtvu4DX0bj9Rv+jjHgfvIvAhcPH0Cc2uZXZ0l8oYbp5tuPz0l4R2RxA1AcPR3Xt8/MP3Wd5bokzmcvWN5+LpYyazUwgFUi+JBGQB1mey43a9opgd4VpP9A3O9bfxBCP+aMQYUbo4fI0QeS0N49+UBq7PwNcSw3o3dc1HPzim3W3Zra5ptxu67YrZ/ARjJqSyRuoFPlqEzs6wUrc0m2s6D4vju1Tvv8e0lhAi/fWWfr0GQMpyML6LqAL6IbR0/9F7+12v/jx4+dGUAOd6NqsLqlmNkIEkW6SU+C5ST5dIu+Pm8T/x/g9+xPFf3icULZ27po0OKWfE3qFESRE102pG2FqePfoXlh88ICiF7bshlFSzvb7Eu35P+uP29xFfDl909URWG2uDUgVCJqbLE1xwRN9SmXJQUMtBiKPxwRK8J8VEu92giwJVmJyRuTfcVQWu6wk+DGPIb8adez0FD+JAUHa2y0WMzGGD+4uVUva7EWkgDg/OoFJm1+MYI1KVQySFAyKqkEiZqOZz2k2D7TcsTu/QrK/ZXjxnenJCOZsRnM2jp+TymEpnbo4UEhlVbsAdlGL5kgghsvlaYiiUItoUw+LUOWG9b0iHkVw/tGTh3S52vgi3o4WUIADBOYSa8OSTT4jtmtpo7pydcfb9v0Evjtl1DSn01LOaEPMDc1of4zcN7eU5ZTWDBNv1itP7D/A7T9c0LO6+Tz0/pd02gxHl0HWSYv8xHPHHYlBNBu8ptETqTGhOMWZum1BEIrv1CikVk8VyCH88QgjHpBZUxQkJTUqK9eUlzeUOKQyigBA6Eg5TapQAU1XMpjNMrYmuYdfs6DvLdtMjpUKpIpuXxji02clF2KGdz7gEvwTypDK75Dc3kbIuKGsoTUXyBc/+5TFPf/lzfvDv/x6fLJ/98mccP3yAqabIYoJWU0Lq0UJh3ZrLzx5h+5blhx/ikkOGhHUBosd1G7yLL/3b48r8KiGUwto2T1eUBK3QpSEki0iS5HPkUyDioyfYHMZrlCZ4h7NuyKsLOXTWemKIw/P7m8NXfU0Fz+3uk0LEtjuq6QKpJMGHQR68j5jIkQ9KZTfVGMOQ7ZNNjEIMw9wQvLV7nThFXWPbDdub59STIybTBTfXL+iaHUVZYeopuiwJcTeMOGUOliwKxECezvEWgyOrzP47udhKmHKevUB8pN/tCCFiygpZGPpmO0h6X8/V/OYhu2gjRHbcHh5KQiROHtzFFPc4Ob2DihbvGqxt6cMOGSD6U5yDEBbYDhCWk/fPOPv2B3z6jz/Fhg4XHKkoidbSW0dKEud89oL4oq7O+DD84/BSER+8P3CypModTiU1Qiq0LgFo1mtSyiqpup6j5ByEBQK6FlTTE4JVrK/WTE6OETqPGUutIEl8kLTbG/CW0OwwhaasDG2XKEyFGmwhtCkJTSAecvDELXdssJAY8YdjsF7NX8dE33QEl5DCcP7pJ1w+OedbP/4r9InHRIO8nrL55yfELmDqiig87WaV7SiqkvnZfabVPXrfEhIEn7C9J/Tt4eA44qtHEpm3uFcrdt1u6MZKpIyHSJm9l1xIkdA1OceukMiiwHZdJjb7iLcWIRS50PlmPfRe/ydO5MVku4ZKTgaewO2RLEu7i4EBniMiQBC8JSUPwoFQKFkQnEMXBc7HbHlfGerJjO7mhoBhvriLtT3Nas3uZst0eYoqaoQKCBVIzg8btUGpbHu/5y3sScjJu8xaj4rmZntQZVXTGoGgW68J3n3T7vtrhSCSRGK/QNLg1CIICBlw3nN+/ggtJWVVoU2JczCfzNjdrFDVEbv1DrFYkJDoqkQag64naD1HV3N2Vy/oe4u9PCclAaj8IJSffy8j/jSkzJcqisxhS2lYq8NPUybyI/ImKZIkBY+pSlLoSU6gtECpinpisN0KXZYUShMbS9f2WCTJe3RyEPIwNIhIURaoIndT+3aX9wb5apGT+8Pjff4yePmaJRFIJJyVrC5XuBj4/k9+gigDqdC06y1CS47u36e9uqZaHiGMwD1pefDxX7O6ekZnN6QyIpTANT19ux2c0uXYhHvNSPs1km7XiLMWUn4GppSyDYgYciGFxCeHczaLhIYFnkU7Q5hr2hc8+1d88/H6C56h0gze0bU7TFVlV+OQ/W72FzzLyPXBjyHzCEAX+nB9pTI463HeUU6mVHUJyVPNFhAk3uZQvNnyDOd62u0Oay8pZ2VWjEWJlrlSTSkOI6mh2zOcXoXK/h85EwvKegYiJw+3mzUxxMP/a9xl/w28fH32qblDO1RIQ0iRGAW28chOIWKF9BGZBNF26FrhYqBvI6UWnH/2gpRqul2L7Z8RUk9SmkyvykW0kOIwTBtvzZ8He9mwdy67KEeBGtresjCkwXerKCuqyRxr1xijs/N5FKSgiE7hY0+SsF5dUi2OKaXBxJx6npRACkX0uZBKUh4MQkOwsB8vf66Fc/jT+DT9k5BgULgJUlIQoJovuL74V3Q5o6yPsF1LURmKI8l6c406OSYgaE1g3V3jYo/tt/jY46wnpQIoMgcTDnvAiNeH335EZdJ/fu5JYhCHwkaIMBQ3ceClyldeJRtDfvPwtXR49l2U4AI29VTTOTlRPQKKFF3O7tSaTLoK+dRI9sMJwTOQcEgCykmJNhohJd7msVc5rVmeTWnWV7S7GxKB43t3cd7Rty3t2iIo8MqTYo9QQwWLQyk3vBeBNiVaKco6q8ty+09kc0G3jyZ47VfxG4XEoL4YNjuRXpYLD/wt1OEhFYODBLvOg0gIZwcVRwMomm1Psz3PppVS4GMg7RUenxthyfHB92dFOsSnQHQpy1CVQChJjA4ApVVWVQJaVYMnlSRJsN4hJZjSEKxFSoPtA6LwSAmqMljX41MkJgEpABJVVMQuDOIFkc0Fud1L8ueKw3sb8eUhAA5K0zBMChUpVfg+4LprIOE6R7fpCKFi/eQ6R7WEmstnF/lVUknoIZG79JI4dOG+OZyPtwEvnwv23lT7wybknvv+B4fdM736/S9eU9+czs4eX/MQNZMh281N5tgUJjshk7tAUioYvI84hwcAAAOHSURBVHdyREQeh6jCkGLC9S314mjYBCMxSLxLxADOBkLpUUoymc2JCdrdNaowLE+P6dsdwSfKepH5BslmeWwcPH+GnCWpdS62QvYMCt7TN9sh6HSsdP4wfInrJLKLw74gAm7X1r43i3jJXG68F68fOYg3WTtwAdJA9s+E4hAixlRZyZji8H0PShIH1V45mbLbbSkLDVJlLlwcQmiVwgVH8D3JWWLKIgZGf52vHIcInle+J1+ymxgOrT535m3bD9+RL8VCjMqrbwZ+1x16++7cG8EaizFg2x0pxaHoyQ6vtxlVYih6hnFXEniXIyS8c7ntPeyB3sUhviCw22wpTT6pmCoTl3c3l3TbVW7HD94wUgliFGgtadsmq1FMSVaLWVxvESmPuPp2RwphKMBuiWAjRrxzGEZHiewynuLAmQpx8NQKkPrbbVMEpCpICKzzhxDhyWyGbXeY6SKrRVImtwfvSQxjSZEfwqM44M1BduC4tRMZWJhf87saMeJ34w0oePJJ/VD0xIgssi/APv4hDq1QIfPYIgSfoyi0OWRYxRTwIeZsFlPjbY+PEXwONfMhhwiW0yOULgcDsyxXl1rinafvdgglKcqh2ImZzxNiwLc9tmvzWx5UK2n0rh/xjmPf5cyk4dwB8D7sf4qzFkH209JCHZRdMeQiSSoBUiAnNda7TBkgj8rSMP7YP0j3QqwRbw7SSx2fl6QnX+M7GjHid+MNKHhgTx1PZPWW8AIznR58eJQ0hxFXDBCTx5STIaAsy9qL0hCCRyqD1AKjquzWnBIpyhxISkQKhdIl5WKKT2usdyhykSQxSCkOYzWhIDhPt93m5PXfYn2N3Z0RI27xBQ+6IYQ0pYS1PWBv/66IiBAhBFIUgIa9mSF76vkoL39TIb7g67HUGfEm4w0peEC8RDYNwdNub6imc0w1OahASDnOXpsyO78OJllCJIQEqbNUVqrsaKjkFB8EQkRSCigpMqdVgdCJclFhmxZpBOU0x1QoisOYant9ge0aog9IZDZDZEh6HzFixAFpb/j3BchmovKVv50Q2csj+YGYPBRGCJIcipwsmjy87NhQHTFixJ8CMXJQRowYMWLEiBFvO0Z94IgRI0aMGDHircdY8IwYMWLEiBEj3nqMBc+IESNGjBgx4q3HWPCMGDFixIgRI956jAXPiBEjRowYMeKtx1jwjBgxYsSIESPeevx/tetfmqWI9LkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x144 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x144 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#@title Visualize Data\n",
    "visualize_tfdataset(ds_train, num_samples=5)\n",
    "visualize_tfdataset(ds_validation, num_samples=5)\n",
    "visualize_tfdataset(ds_test, num_samples=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "K6BdSLZmsCNy"
   },
   "source": [
    "### Model Definition\n",
    "\n",
    "Implementations of tuned [baselines](https://github.com/OATML/bdl-benchmarks/tree/alpha/baselines/diabetic_retinopathy_diagnosis) are provided for each benchmark, as well as their [leaderboards](https://github.com/OATML/bdl-benchmarks/tree/alpha/leaderboard/diabetic_retinopathy_diagnosis).\n",
    "\n",
    "For this colab, we implement a naive 1-hidden layer feedforward neural network in [`TensorFlow 2.0`](https://www.tensorflow.org/beta/) to illustrate the workflow, using Monte Carlo Dropout for estimating the predictive entropy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "cellView": "both",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 357
    },
    "colab_type": "code",
    "id": "0GYQjCLH_qhh",
    "outputId": "a2156523-1340-4c27-d805-30bc2195b9bb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "flatten (Flatten)            (None, 196608)            0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 32)                6291488   \n",
      "_________________________________________________________________\n",
      "activation (Activation)      (None, 32)                0         \n",
      "_________________________________________________________________\n",
      "dropout (Dropout)            (None, 32)                0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 1)                 33        \n",
      "_________________________________________________________________\n",
      "activation_1 (Activation)    (None, 1)                 0         \n",
      "=================================================================\n",
      "Total params: 6,291,521\n",
      "Trainable params: 6,291,521\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "classifier = tfk.Sequential([\n",
    "    tfkl.InputLayer(input_shape),\n",
    "    tfkl.Flatten(),\n",
    "    tfkl.Dense(units=32, kernel_regularizer=tfk.regularizers.l2(l2_reg)),\n",
    "    tfkl.Activation(\"relu\"),\n",
    "    tfkl.Dropout(DROPOUT_RATE),\n",
    "    tfkl.Dense(units=1, kernel_regularizer=tfk.regularizers.l2(l2_reg)),\n",
    "    tfkl.Activation(\"sigmoid\"),\n",
    "])\n",
    "classifier.compile(loss=dtask.loss(),\n",
    "                   optimizer=tfk.optimizers.Adam(learning_rate),\n",
    "                   metrics=dtask.metrics())\n",
    "classifier.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 445
    },
    "colab_type": "code",
    "id": "tFEW2FcvBq0V",
    "outputId": "b86bf5ab-cbeb-445b-b69f-49868c885c41"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "WARNING:tensorflow:From /scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorflow/python/ops/math_grad.py:1250: add_dispatch_support.<locals>.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.where in 2.0, which has the same broadcast rule as np.where\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /scratch-ssd/oatml/miniconda3/envs/bdlb/lib/python3.6/site-packages/tensorflow/python/ops/math_grad.py:1250: add_dispatch_support.<locals>.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.where in 2.0, which has the same broadcast rule as np.where\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5/5 [==============================] - 1s 281ms/step - loss: 8.2383 - binary_accuracy: 0.4250 - auc: 0.4679 - val_loss: 12.4631 - val_binary_accuracy: 0.1875 - val_auc: 0.5000\n",
      "Epoch 2/10\n",
      "5/5 [==============================] - 0s 86ms/step - loss: 12.6555 - binary_accuracy: 0.1750 - auc: 0.5000 - val_loss: 12.4649 - val_binary_accuracy: 0.1875 - val_auc: 0.5000\n",
      "Epoch 3/10\n",
      "5/5 [==============================] - 0s 78ms/step - loss: 12.6571 - binary_accuracy: 0.1750 - auc: 0.5000 - val_loss: 12.2745 - val_binary_accuracy: 0.2000 - val_auc: 0.5000\n",
      "Epoch 4/10\n",
      "5/5 [==============================] - 0s 81ms/step - loss: 12.0833 - binary_accuracy: 0.2125 - auc: 0.5000 - val_loss: 12.2755 - val_binary_accuracy: 0.2000 - val_auc: 0.5000\n",
      "Epoch 5/10\n",
      "5/5 [==============================] - 0s 86ms/step - loss: 12.2758 - binary_accuracy: 0.2000 - auc: 0.5000 - val_loss: 12.2762 - val_binary_accuracy: 0.2000 - val_auc: 0.5000\n",
      "Epoch 6/10\n",
      "5/5 [==============================] - 0s 78ms/step - loss: 12.6597 - binary_accuracy: 0.1750 - auc: 0.5000 - val_loss: 12.4683 - val_binary_accuracy: 0.1875 - val_auc: 0.5000\n",
      "Epoch 7/10\n",
      "5/5 [==============================] - 0s 82ms/step - loss: 12.6601 - binary_accuracy: 0.1750 - auc: 0.5000 - val_loss: 12.4686 - val_binary_accuracy: 0.1875 - val_auc: 0.5000\n",
      "Epoch 8/10\n",
      "5/5 [==============================] - 0s 84ms/step - loss: 10.7437 - binary_accuracy: 0.3000 - auc: 0.5000 - val_loss: 12.2771 - val_binary_accuracy: 0.2000 - val_auc: 0.5000\n",
      "Epoch 9/10\n",
      "5/5 [==============================] - 0s 75ms/step - loss: 13.2355 - binary_accuracy: 0.1375 - auc: 0.5000 - val_loss: 12.2772 - val_binary_accuracy: 0.2000 - val_auc: 0.5000\n",
      "Epoch 10/10\n",
      "5/5 [==============================] - 0s 80ms/step - loss: 13.0439 - binary_accuracy: 0.1500 - auc: 0.5000 - val_loss: 12.2772 - val_binary_accuracy: 0.2000 - val_auc: 0.5000\n"
     ]
    }
   ],
   "source": [
    "#@title Train Model\n",
    "history = classifier.fit(\n",
    "    ds_train,\n",
    "    epochs=NUM_EPOCHS,\n",
    "    steps_per_epoch=5,\n",
    "    validation_data=ds_validation,\n",
    "    validation_steps=5,\n",
    "    class_weight=dtask.class_weight(),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "CV4IsR9qtWNJ"
   },
   "outputs": [],
   "source": [
    "def predict(x):\n",
    "  \"\"\"Monte Carlo dropout uncertainty estimator.\n",
    "  \n",
    "  Args:\n",
    "    x: `numpy.ndarray`, datapoints from input space,\n",
    "      with shape [B, H, W, 3], where B the batch size and\n",
    "      H, W the input images height and width accordingly.\n",
    "\n",
    "  Returns:\n",
    "    mean: `numpy.ndarray`, predictive mean, with shape [B].\n",
    "    uncertainty: `numpy.ndarray`, ncertainty in prediction,\n",
    "      with shape [B].\n",
    "  \"\"\"\n",
    "  # Get shapes of data\n",
    "  B, _, _, _ = x.shape\n",
    "\n",
    "  # Monte Carlo samples from different dropout mask at test time\n",
    "  mc_samples = np.asarray(\n",
    "      [classifier(x, training=True)\n",
    "       for _ in range(NUM_MCDROPOUT_SAMPLES)]).reshape(-1, B)\n",
    "\n",
    "  # Bernoulli output distribution\n",
    "  dist = scipy.stats.bernoulli(mc_samples.mean(axis=0))\n",
    "\n",
    "  # Predictive mean calculation\n",
    "  mean = dist.mean()\n",
    "\n",
    "  # Use predictive entropy for uncertainty\n",
    "  uncertainty = dist.entropy()\n",
    "  \n",
    "  return mean, uncertainty"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "pcprhAdbA75g"
   },
   "source": [
    "### Evaluate Model\n",
    "\n",
    "Machine learning researchers often evaluate their predictions directly on the whole test set.\n",
    "But, in fact, in real-world settings we have additional choices available, like asking for more information when we are uncertain.\n",
    "Because of the importance of accurate diagnosis, it would be unreasonable _not_ to ask for further scans of the most ambiguous cases.\n",
    "Moreover, in this dataset, many images feature camera artefacts that distort results.\n",
    "In these cases, it is critically important that a model is able to tell when the information provided to it is not sufficiently reliable to classify the patient.\n",
    "Just like real medical professionals, any diagnostic algorithm should be able to flag cases that require more investigation by medical experts.\n",
    "\n",
    "<p align=\"center\">\n",
    "<img src=\"http://www.cs.ox.ac.uk/people/angelos.filos/assets/bdl-benchmarks/diagnosis.png\" >\n",
    "</p>\n",
    "\n",
    "This task is illustrated in the figure above, where a threshold, τ, is used to flag cases as certain and uncertain, with uncertain cases referred to an expert. Alternatively, the uncertainty estimates could be used to come up with a priority list, which could be matched to the available resources of a hospital, rather than waste diagnostic resources on patients for whom the diagnosis is clear cut.\n",
    "\n",
    "In order to simulate this process of referring the uncertain cases to experts and relying on the model's predictions for cases it is certain of, we assess the techniques by their diagnostic accuracy and area under receiver-operating-characteristic (ROC) curve, as a function of the\n",
    "referral rate. We expect the models with well-calibrated uncertainty to refer their least confident predictions to experts,\n",
    "improving their performance as the number of referrals increases.\n",
    "\n",
    "The accuracy of the binary classifier is defined as the ratio of correctly classified data-points over the size of the population.\n",
    "The receiver-operating-characteristic (ROC) curve illustrates\n",
    "the diagnostic ability of a binary classifier system as its discrimination threshold is varied.\n",
    "It is created by plotting the true positive rate (a.k.a. sensitivity) against the false positive rate (a.k.a. 1 - sensitivity).\n",
    "The quality of such a ROC curve can be summarized by its area under the curve (AUC), which varies between 0.5 (chance level) and 1.0 (best possible value)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 594
    },
    "colab_type": "code",
    "id": "uz0mbQTtqfun",
    "outputId": "a209e31e-2ed9-41d0-8601-ca70de2074ac"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "10it [00:01,  8.91it/s]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "results = dtask.evaluate(predict,\n",
    "                         dataset=ds_test.take(10),\n",
    "                         name=\"naive_method\")\n",
    "leaderboard(\"diabetic_retinopathy_diagnosis\",\n",
    "            results,\n",
    "            leaderboard_dir=\"leaderboard\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "ewIGzk-N5YM2"
   },
   "source": [
    "| Method              | AUC<br>(50% data retained)  | Accuracy<br>(50% data retained) | AUC<br>(100% data retained) | Accuracy<br>(100% data retained) |\n",
    "| ------------------- | :-------------------------: | :-----------------------------: | :-------------------------: | :-------------------------------: |\n",
    "| Ensemble MC Dropout | 88.1 ± 1.2                  | 92.4 ± 0.9                      | 82.5 ± 1.1                  | 85.3 ± 1.0                        |\n",
    "| MC Dropout          | 87.8 ± 1.1                  | 91.3 ± 0.7                      | 82.1 ± 0.9                  | 84.5 ± 0.9                        |\n",
    "| Deep Ensembles      | 87.2 ± 0.9                  | 89.9 ± 0.9                      | 81.8 ± 1.1                  | 84.6 ± 0.7                        |\n",
    "| Mean-field VI       | 86.6 ± 1.1                  | 88.1 ± 1.1                      | 82.1 ± 1.2                  | 84.3 ± 0.7                        |\n",
    "| Deterministic       | 84.9 ± 1.1                  | 86.1 ± 0.6                      | 82.0 ± 1.0                  | 84.2 ± 0.6                        |\n",
    "| Random              | 81.8 ± 1.2                  | 84.8 ± 0.9                      | 82.0 ± 0.9                  | 84.2 ± 0.5                        |"
   ]
  }
 ],
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  "accelerator": "GPU",
  "colab": {
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   "name": "Copy of bdlb.ipynb",
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  "kernelspec": {
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